Identification of genetic markers of biological age and metabolism

ABSTRACT

A method of measuring the biological age of a multicellular organism is disclosed. In one embodiment this method comprises the steps of obtaining a sample of nucleic acid isolated from the organism&#39;s organ, tissue or cell and determining the expression pattern of a panel of sequences within the nucleic acid that have been predetermined by either increase or decrease in response to biological aging of the organ, tissue or cell. A method of obtaining biomarkers of aging is also disclosed. This method comprises the step of comparing a gene expression profile of a young multicellular organism subject&#39;s organ, tissue or cells; a gene expression profile from a chronologically aged subject&#39;s organ, tissue or cell; and a gene expression profile from a chronologically aged but biologically younger subject&#39;s organ, tissue or cell and identifying gene expression alterations that are observed when comparing the young subjects and the chronologically aged subjects and are not observed or reduced in magnitude when comparing the young subjects and the chronologically aged but biologically younger subjects.

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims priority to provisional application60/148,540, filed Aug. 12, 1999, U.S. provisional application60/178,232, filed Jan. 26, 2000 and 60/211,923 filed Jun. 16, 2000.These provisional applications are incorporated by reference as if fullyset forth herein.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT

[0002] This invention was made with United States government supportawarded by the following agencies: NIH Grant No: AG11915. The UnitedStates has certain rights in this invention.

BACKGROUND OF THE INVENTION

[0003] A common feature of most multicellular organisms is theprogressive and irreversible physiological decline that characterizessenescence. Although genetic and environmental factors can influence theaging process, the molecular basis of senescence remains unknown.Postulated mechanisms include cumulative damage to DNA leading togenomic instability, epigenetic alterations that lead to altered geneexpression patterns, telomere shortening in replicative cells, oxidativedamage to critical macromolecules and nonenzymatic glycation oflong-lived proteins (S. M. Jazwinski, Science 273:54, 1996; G. M.Martin, et al., Nature Gen. 13:25, 1996; F. B. Johnson, et al., Cell96:291, 1996; K. B. Beckman and B. N. Ames, Physiol. Revs. 78:547,1998). Factors which contribute to the difficulty of elucidatingmechanisms and testing interventions include the complexity oforganismal senescence and the lack of molecular markers of biologicalage (biomarkers). Aging is complex in that underlying mechanisms intissues with limited regenerative capacities (e.g., skeletal and cardiacmuscle, brain), which are composed mainly of postmitotic (non-dividing)cells, may differ markedly from those operative in proliferativetissues. Accordingly, approaches which provide a global assessment ofsenescence in specific tissues would greatly increase understanding ofthe aging process and the possibility of pharmaceutical, genetic ornutritional intervention.

[0004] Genetic manipulation of the aging process in multicellularorganisms has been achieved in Drosophila, through the over-expressionof catalase and Cu/Zn superoxide dismutase (W. C. Orr and R. S. Sohal,Science 263:1128, 1994; T. L. Parkes, et al., Nat. Genet. 19:171, 1998),in the nematode C. elegans, through alterations in the insulin receptorsignaling pathway (S. Ogg, et al., Nature 389:994, 1997; S. Paradis andG. Ruvkun, Genes Dev. 12:2488-2498, 1998; H. A. Tissenbaum and G.Ruvkun, Genetics 148:703, 1998), and through the selection ofstress-resistant mutants in either organism (T. E. Johnson, Science249:908, 1990; S. Murakami and T. E. Johnson, Genetics 143:1207, 1996;Y. J. Lin, et al., Science 282:943, 1998). In mammals, there has beenlimited success in the identification of genes that control aging rates.Mutations in the Werner Syndrome locus (WRN) accelerate the onset of asubset of aging-related pathology in humans, but the role of the WRNgene product in the modulation of normal aging is unknown (C. E. Yu, etal., Science 272:258, 1996; D. B. Lombard and L. Guanrente, TrendsGenet. 12:283, 1996).

[0005] In contrast to the current lack of genetic interventions toretard the aging process in mammals, caloric restriction (CR) appears toslow the intrinsic rate of aging (R. Weindruch and R. L. Walford, TheRetardation of Aging and Disease by Dietary Restriction (CC. Thomas,Springfield, Ill., 1988; L. Fishbein, Ed., Biological Effects of DietaryRestriction (Springer-Verlag, New York, 1991; B. P. Yu, Ed., Modulationof Aging Processes by Dietary Restriction (CRC Press, Boca Raton, Fla.1994). Most studies have involved laboratory rodents which, whensubjected to a long-term, 25-50% reduction in calorie intake withoutessential nutrient deficiency, display delayed onset of age-associatedpathological and physiological changes and extension of maximumlifespan.

BRIEF SUMMARY OF THE INVENTION

[0006] The present invention will allow the evaluation of aginginterventions on a molecular and tissue-specific basis through theidentification of aging biomarkers. In particular, the use of geneexpression profiles allows the measurement of aging rates of targetorgans, tissues and cells, and to what extent aging is delayed byspecific interventions, as determined by quantitative analysis of mRNAabundance. Because aging-related gene expression profiles can beclassified in subgroups according to function, the invention also allowsfor the determination of how function-specific aspects of aging areaffected. This particular feature will allow for determination ofcombination therapies that prevent or reverse most aging related changesin particular organs, tissues, and cells.

[0007] In one embodiment, the present invention is a method of measuringthe biological age of a multicellular organism comprising the steps of(a) obtaining a sample of nucleic acid isolated from the organism'sorgan, tissue or cell, wherein the nucleic acid is RNA or a cDNA copy ofRNA and (b) determining the expression pattern of a panel of sequenceswithin the nucleic acid that have been predetermined to either increaseor decrease in response to biological aging of the organ, tissue orcell. Preferably, the expression patterns of at least ten sequences aredetermined in step (b) and the organism is a mammal, most preferably arodent.

[0008] In one preferred embodiment of the method described above, thenucleic acid is isolated from a mammalian tissue selected from the groupconsisting of brain tissue, heart tissue, muscle tissue, skin, livertissue, blood, skeletal muscle, lymphocytes and mucosa.

[0009] In another embodiment the present invention is a method ofobtaining biomarkers of aging comprising the steps of: (a) comparing agene expression profile of a young multicellular organism subject'sorgan, tissue or cells; a gene expression profile from a chronologicallyaged (and therefore biologically aged) subject's organ, tissue or cell;and a gene expression profile from a chronologically aged butbiologically younger subject's organ, tissue or cell, and (b)identifying gene expression alterations that are observed when comparingthe young subjects and the chronologically aged subjects and are notobserved or reduced in magnitude when comparing the young subjects andchronologically aged and biologically younger subjects. Preferably, oneuses high density oligonucleotide arrays comprising at least 5-10% ofthe subject's gene expression product to compare the subject's geneexpression profile, and caloric restriction to obtain a chronologicallyaged but biologically younger subject.

[0010] In a preferred embodiment of the method described above, the geneexpression profile indicates a two-fold or greater increase or decreasein the expression of certain genes in biologically aged subjects. In amore preferred embodiment of the present invention, the gene expressionprofile indicates a three-fold or greater or, most preferably three-foldor greater, increase or decrease in the expression of certain genes inaged subjects.

[0011] In another embodiment, the present invention is a method ofmeasuring biological age of muscle tissue comprising the step ofquantifying the mRNA abundance of a panel of biomarkers selected fromthe group consisting of markers described in the Tables 1, 2, 15 and 16.A method of measuring biological age of brain tissue comprising the stepof quantifying the mRNA abundance of a panel of biomarkers selected fromthe group consisting of markers described in Tables 5, 6, 9, 10, 11, 12,13 and 14.

[0012] In another embodiment, the present invention is a method forscreening a compound for the ability to inhibit or retard the agingprocess in a multicellular organism tissue, organ or cell, preferablymammalian tissue, organ or cell, comprising the steps of: (a) dividingtest organisms into first and second samples; (b) administering a testcompound to the organisms of the first sample; (c) analyzing tissues,organisms and cells of the first and second samples for the level ofexpression of a panel of sequences that have been predetermined toeither increase or decrease in response to biological aging of thetissue, (d) comparing the analysis of the first and second samples andidentifying test compounds that modify the expression of the sequencesof step (c) in the first sample such that the expression pattern isindicative of tissue that has an inhibited or retarded biological age.

[0013] It is an object of the present invention to evaluate or screencompounds for the ability to inhibit or retard the aging process.

[0014] It is also an object of the present invention to measure thebiological age of a multicellular organism, such as a mammal in a tissueor cell-specific basis.

[0015] It is also an object of the present invention to obtainbiomarkers of aging.

[0016] Other objects, features and advantage of the present inventionwill become apparent to one of skill in the art after review of thespecification and claims.

DETAILED DESCRIPTION OF THE INVENTION

[0017] One of the major impediments to the development ofpharmaceutical, genetic or nutritional interventions aimed at retardingthe aging process is the lack of a molecular method for measuring theaging process in humans or experimental animals. A suitable biomarker ofthe aging process should reflect biological age (physiologicalcondition) as opposed to chronological age. Additionally, the biomarkershould be amenable to quantitation, and reflect aging-relatedalterations at the molecular level in the tissue under study.Importantly, any such biomarker must be validated with the use of amodel of retarded aging.

[0018] Caloric restriction, when started either early in life or inmiddle-age, represents the only established paradigm of agingretardation in mammals. (R. Weindruch and R. L. Walford, “TheRetardation of Aging and Disease by Dietary Restriction” (C. C. Thomas,Springfield, Ill, 1988)) The effects of caloric restriction onage-related parameters are broad: caloric restriction increases mean andmaximum lifespan, reduces and delays both spontaneous and inducedcarcinogenesis, almost completely suppresses autoimmunity associatedwith aging, and reduces the incidence of several age-induced diseases.(R. Weindruch and R. L. Walford, supra, 1988) Therefore, we expect thatthe rate of change of most proposed aging biomarkers should be retardedby caloric restriction.

[0019] By “biological age” we mean the physiological state of an animalor tissue relative to the physiological changes that occur throughoutthe animal's lifespan. By “chronological age” we mean the age of ananimal as measured by a time scale such as month or years.

[0020] Because gene expression patterns are responsive to bothintracellular and extracellular events, we reasoned that simultaneousmonitoring of thousands of genes on a tissue-specific or organ-specificbasis would reveal a set of genes that are altered in expression levelsas a consequence of biological aging. Although alterations in geneexpression with aging had been previously investigated for some genes, aglobal analysis of gene expression patterns during aging, and thevalidation of such patterns as a tool to measure biological age throughthe use of a model of retarded aging had not been previously performed.Such global analysis is required to identify genes that are expresseddifferentially as a consequence of aging on different cell types thatcompose the tissue under study and will allow a quantitative assessmentof aging rates.

[0021] There exists a large and growing segment of the population indeveloped countries that is suffering from age-associated disorders,such as sarcopenia (loss of muscle mass), neurodegenerative conditions,and cardiac disease. Therefore, the market for compounds that preventaging-associated disorders and improve quality of life for the elderlyis likely to drive research and development of novel drugs by thepharmaceutical industry. As an example, many drugs, nutraceuticals andvitamins are thought to influence aging favorably, but their use remainslimited due to the lack of FDA approval. The inability to assessbiological aging in tissues at the molecular level precludes properanimal and human testing of such compounds.

[0022] In one embodiment, the invention is a method for measuring thebiological aging process of a multicellular organism, such as a mammal,at the organ, tissue or cellular level through the characterization ofthe organism's gene expression patterns. This method preferablycomprises obtaining a cDNA copy of the organism's RNA and determiningthe expression pattern of a panel of particular sequences (preferably atleast 5 sequences, most preferably at least 10 sequences and morepreferably at least 20, 30, 40, or 50 sequences) within the cDNA thathave been predetermined to either increase or decrease in response tobiological aging of the organ, tissue or cell. (We refer to nucleotidesequences with alterartions in expression patterns characteristic ofbiological age as “biomarkers.”) One may characterize the biological ageof the organism by determining how many and at what level the biomarkersare altered.

[0023] Tables 1-4 and 15-16 describe a specific gene expression profilesdetermined in skeletal muscle of mice. Tables 1, 2, 15 and 16 describeaging-related increases and decreases in gene expression ingastrocnemius of mice. (Tables 1 and 2 were prepared using a highdensity oligonucleotide array of over 6,300 genes, while Tables 15 and16 were prepared using a high density oligonucleotide array of 19,000genes.) Tables 3 and 4 describe caloric restriction related decreasesand increases in gene expression. Tables 1 and 2 contain a column (“CRreversal”) describing the influence of caloric restriction on theincreased or decreased expression. Tables 5-8 describe a similaranalysis of the gene expression profile determined neocortex tissue ofmice and Tables 9 and 10 describe a gene expression profile determinedon the cerebellum tissue in mice. Tables 11-14 describe gene expressionprofiles determined in mouse heart. (Tables 11 and 12 were prepared withthe 19,000 high density oligonucleotide chip, while Tables 13 and 14were prepared using the less dense gene chip.) From these geneexpression profiles, one may select many biomarkers.

[0024] For example, in order to either measure or determine biologicalage in skeletal muscle, one would select markers in Tables 1 and 2 thatreflect changes in gene expression that have been shown to be eitherpartially or completely inhibited by caloric restriction in skeletalmuscle such as AA0071777, L06444, AA14576, etc. Genes that were notaffected by caloric restriction (such as W84988, Table 1) may representchronological markers or aging, and therefore are less useful for themeasurement of aging rates. One may determine which genes are or are notaffected by caloric restriction by examination of the “CR reversal” laneof Tables 1 or 2.

[0025] If one wished to examine a tissue, organ or cell that is notrepresented in Tables 1-16, one would prepare samples and tabulateresults from those samples as described below in the Examples. In thismanner, one may examine any tissue, organ or cell for biological aging.Preferably, one would wish to examine a tissue selected from the groupconsisting of brain tissue, heart tissue, muscle tissue, skin, livertissue, blood, lymphocytes, skeletal tissue and mucosa.

[0026] For example, choosing markers from Tables 1 and 2 to examine theefficacy of a test compound in aging prevention, one could design aPCR-based amplification strategy or a DNA microarray hybridizationstrategy to quantify the mRNA abundance for markers W08057, AA114576,11071777, 11106112, D29016 and M16465 as a function of aging, usinganimals of several age groups, such as 6 months, 12 months, 18 months,24 months and 30 months. (The marker designations refer to Gene Bankaccession number entries.) A second set of animals would be given a testcompound intended to slow the aging process at 10 months of age (middleage). Animals from the experimental group would be sacrificed orbiopsied at the ages of 12 months, 18 months, 24 months and 30 months.If the test compound is successful, the normal aging-related alterationsin expression of these particular markers will be prevented orattenuated.

[0027] One would follow the same protocol in using the other tables formarker selection. One would match the tissue to be analyzed with theappropriate table. For example, if one were analyzing muscle tissue, onemight choose markers from Tables 1 and 2.

[0028] In another embodiment, the present invention is a method ofobtaining and validating novel mammalian biomarkers of aging.Preferably, this method comprises the steps of comparing the geneexpression profile from a young subject's organ, tissue or cells withsamples from individuals that are both chronologically and biologicallyaged. This is followed by comparison of the gene expression profile ofthe chronologically and biologically aged individuals with that ofindividuals that display similar chronological ages, but a youngerbiological age, such as animals under caloric restriction. Geneexpression alterations that are prevented or retarded by caloricrestriction represent markers of biological age, as opposed tochronological age.

[0029] In one version of this embodiment, one would preferably use highdensity oligonucleotide arrays representing at least 5-10% of thesubject's genes, as described in Lee, et al. at Science285(5432):1390-1393, 1999 and Lee, et al., Nat. Genet. 25(3):294-297,2000. (Both Lee, et al., supra, 1999 and Lee, et al., supra, 2000 areincorporated by reference as if fully set forth herein.)

[0030] For example, Lee, et al., supra, 1999 details the comparisonbetween gastrocnemius muscle from 5 month (young) and 30 month (aged)mice, and 30 month mice under caloric restriction. Lee, et al., supra,1999 disclose that of the 6500 genes surveyed in the oligonucleotidearray, 58 (0.9%) displayed a greater than 2-fold increase in expressionlevels as a function of age and 55 (0.8%) displayed a greater than2-fold decrease in expression. The most substantial expression changewas for the mitochondrial sarcomeric creatine kinase (Mi-CK) gene(3.8-fold). Sequences that display a greater than three-fold alteration(increase or decrease) with aging, which are prevented or restricted bycaloric restriction, such as W08057, AA114576, AA071777, AA106112,D29016, M16465, are likely to be particularly good aging biomarkers.

[0031] Lee, et al., supra, 2000 describes the comparison between cDNAsisolated from neocortex tissue for the same three groups of micedescribed above. Lee, et al., supra, 2000 disclose that of the 6347genes surveyed, 63 (1%) displayed a greater than 1.7-fold increase inexpression levels with aging in the neocortex, whereas 63 genes (1%)displayed a greater than 2.1-fold increase in expression in thecerebellum. Functional classes were assigned and regulatory mechanismsinferred for specific sets of alterations (see Tables 5-10). Of these,20% (13/63), and 33% (17-51) could be assigned to an inflammatoryresponse in the neocortex and cerebullum, respectively. Transcriptionalalterations of several genes in this category were shared by the twobrain regions, although fold-changes tended to be higher in thecerebellum, perhaps due to reduced tissue size and/or reducedheterogeneity at the cellular level. These transcriptional alterationsinclude the microglial and macrophage migration factor Mps1 and theCd40L receptor, which is a mediator of the microglial activationpathway. Also induced was Lysozyme C and beta(2) microglobulin which aremarkers of inflammation in the human CNS. Interestingly, a concertedinduction of the complement cascade components C4, C1qA, C1qB and C1qCwas observed, a part of the humoral immune system involved ininflammation and cytolysis.

[0032] In another embodiment, the present invention is a method ofscreening a test compound for the ability to inhibit or retard the agingprocess in mammalian tissue. In a typical example of this embodiment,one would first treat a test mammal with a test compound and thenanalyze a representative tissue of the mammal for the level ofexpression of a panel of biomarkers. Preferably, the tissue is selectedfrom the group consisting of brain tissue, heart tissue, muscle tissue,blood, skeletal muscle, mucosa, skin and liver tissue. One then comparesthe analysis of the tissue with a control, untreated mammal andidentifies test compounds that are capable of modifying the expressionof the biomarker sequences in the mammalian samples such that theexpression is indicative of tissue that has an inhibited or retardedbiological age. This expression pattern would be more similar to anexpression pattern found in biologically younger subjects.

[0033] As an example, a group of young rodents (mice) would be dividedinto a control and a test group. The test group would receive a testcompound as a dietary supplement added to food from age 5 months to 30months, whereas the control group would receive a standard diet duringthis time period. At age 30 months, several tissues would be collectedfrom animals from each group, and a gene expression profile would beobtained. Each animal's gene expression profile would be compared tothat of a 5 month (young) animals receiving the standard diet. One wouldthen examine if, for any of the organs investigated, the gene expressionpattern fo the animals receiving the test compound was more similar tothat of young animals, compared to the experimental group that receiveda standard diet.

[0034] In another embodiment, the present invention is a method ofdetecting whether a test compound mimics the gene profile induced bycaloric restriction. This method typically comprises the steps ofexposing the mammal to a test compound and measuring the level of apanel of biomarkers. One then determines whether the expression patternof the tissue mimics the expression pattern induced by caloricrestriction.

[0035] For example, if one wished to examine skeletal muscle, the testcompound would be analyzed for induction of genes observed to be inducedby caloric restriction in Tables 3 and 4.

EXAMPLES

[0036] 1. In General

[0037] In order to test our hypothesis, we performed gene expressionprofiling of over 6300 genes in skeletal muscle, neocortex tissue, andcerebellum tissue and 19,000 genes in skeletal muscle and heart tissueof 5-month and 30-month old C57Bl6 mice, using high densityoligonucleotide arrays. We found that a number of genes demonstratedalterations in gene expression profile as a function of chronologicalage and that these genes were broadly divided into a few classes listedin the Tables, such as stress response, energy metabolism, biosynthesis,protein metabolism and neuronal growth.

[0038] In order to validate the use of gene expression profiles asbiomarkers of biological age, we investigated the role of caloricrestriction, the only intervention known to retard the aging process inmammals, on gene expression profiles. Our analysis demonstrated that30-month old calorically restricted animals display either complete orpartial prevention of most aging associated alterations in geneexpression, validating the use of gene expression profiles as abiomarkers of the aging process. In the process we have discovered agene expression profile that is specifically associated with caloricrestriction. We believe that this profile provides genetic markers forthis metabolic state.

[0039] In like fashion, the present invention allows the determinationof biological age in any organism through the determination ofage-related variations in mRNA abundance. Such determination can beachieved through generation of cDNA from the mRNA of the organism andquantification of the cDNA product through hybridization to DNAmicroarrays, preferably as described here. Alternatively, any techniquethat allows for the quantitative determination of mRNA abundance may beused, such as quantitative PCR, Northern blotting and RNAse protectionassays.

[0040] 2. Experimental Protocols

[0041] Details on the methods employed to house and feed male C57BL/6mice, a commonly used model in aging research with an average lifespanof ˜30 months, were recently described (T. D. Pugh, et al., Cancer Res.59:642, 1999). Briefly, mice were purchased from Charles RiverLaboratories (Wilmington, Mass.) at 1.5 months of age. After receipt inMadison, the mice were housed singly in the specific pathogen-freeShared Aging Rodent Facility at the Madison Veterans AdministrationGeriatric Research, Education and Clinical Center, and provided anon-purified diet (PLI5001 (Purina Labs, St. Louis, Mo.) and acidifiedwater ad libitum for one week. The mice were then allocated into twogroups and fed one of two nearly isocaloric (˜4.1 kcal/g), semi-purifieddiets. Each mouse in the control group was fed 84 kcal/week of thecontrol diet (TD91349 (Teklad, Madison, Wis.)) which is ˜5-20% less thanthe range of individual ad libitum intakes. This dietary intake was usedso that the control mice were not obese and retained motor activity upto the age of sacrifice. Each mouse subjected to CR was fed 62 kcal/weekof the restricted diet (TD9351 (Teklad, Madison, Wis.)), resulting in a26% reduction of caloric intake. The latter diet was enriched inprotein, vitamins and minerals such that caloric restriction (CR) andcontrol mice were fed nearly identical amounts of these components. Thefat component, corn oil, was at the same level (13.5%) in both diets,leading to a 26% reduction in fat intake for the calorie-restrictedmice. The adult body weights of the mice averaged ˜32 g for controls and˜23 g for those on CR. Mice were euthanized by rapid cervicaldislocation, autopsied to exclude animals showing overt disease, and thegastrocnemius muscle was removed from each limb, combined in amicocentrifuge tube, and immediately flash-frozen in liquid nitrogen andthen stored at −80° C. All aspects of animal care were approved by theappropriate committees and conformed with institutional guidelines.

[0042] Total RNA was extracted from frozen tissue using TRIZOL reagent(Life Technologies) and a power homogenizer (Fisher Scientific) with theaddition of chloroform for the phase separation before isopropyl alcoholprecipitation of total RNA. Poly(A)⁺ RNA was purified from the total RNAwith oligo-dT linked Oligotex resin (Qiagen). One microgram of poly(A)⁺RNA was converted into double-stranded cDNA (ds-cDNA) using SuperScriptChoice System (Life Technologies) with an oligo dT primer containing aT7 RNA polymerase promoter region (Genset). After second strandsynthesis, the reaction mixture was extracted withphenol/chloroform/isoamyl alcohol. Phase Lock Gel (5 Prime→3 Prime,Inc.) was used to increase ds-cDNA recovery. The ds-cDNA was collectedby ethanol precipitation. The pellet was resuspended in 3 μl ofDEPC-treated water. In vitro transcription was performed using a T7Megascript Kit (Ambion) with 1.5 μl of ds-cDNA template in the presenceof a mixture of unlabeled ATP, CTP, GTP, and UTP and biotin-labeled CTPand UTP (bio-11 -CTP and bio-16-UTP (Enzo)). Biotin-labeled cRNA waspurified using a RNeasy affinity column (Quiagen). The amount ofbiotin-labeled cRNA was determined by measuring absorbance at 260 nm.Biotin-labeled cRNA was fragmented randomly to sizes ranging from 35 to200 bases by incubating at 94° C. for 35 minutes in 40 mM Tris-acetatepH 8.1, 100 mM potassium acetate, and 30 mM magnesium acetate. Thehybridization solutions contained 100 mM MES, 1 M (Na⁺), 20 mM EDTA, and0.1% Tween 20. In addition, the hybridization solutions contained 50 pMoligonucleotide B2 (a biotin-labeled control oligonucleotide used formaking grid alignments), 0.1 mg/mL herring sperm DNA, and 0.5 mg/mLacetylated BSA. The final concentration of fragmented cRNA was 0.05μg/μl in the hybridization solutions. Hybridization solutions wereheated to 99° C. for 5 minutes followed by 45° C. for 5 minutes beforebeing placed in the gene chip. 10 μg of cRNA was placed in the genechip. Hybridizations were carried out at 45° C. for 16 hours with mixingon a rotisserie at 60 rpm. Following hybridization, the hybridizationsolutions were removed, and the gene chips were installed in fluidicssystems for wash and stain. The fluidics system (Affymetrix GeneChipFluidics tation 400) performed two post-hybridization washes (anon-stringent wash and a stringent wash), staining withstreptavidin-phycoerythrin, and one post-stain wash. The gene chips wereread at a resolution of 6 μm using a Hewlett Packard Gene array scanner.Data collected from two scanned images were used for the analysis.

[0043] Detailed protocols for data analysis of Affymetrix microarraysand extensive documentation of the sensitivity and quantitative aspectsof the method have been described (D. J. Lockhart, Nature Biotech.14:1675, 1996). The Affymetrix GeneChip MU6500 set was derived fromselected genes and ESTs from the Aug. 15, 1996 release of GeneBank.Briefly, each gene is represented by the use of ˜20 perfectly matched(PM) and mismatched (MM) control probes. The MM probes act asspecificity controls that allow the direct subtraction of bothbackground and cross-hybridization signals. The number of instances inwhich the PM hybridization signal is larger than the MM signal iscomputed along with the average of the logarithm of the PM:MM ratio(after background subtraction) for each probe set. These values are usedto make a matrix-based decision concerning the presence or absence of anRNA molecule. All calculations are performed by Affymetrix software. Todetermine the quantitative RNA abundance, the average of the differencesrepresenting PM minus MM for each gene-specific probe family iscalculated, after discarding the maximum, the minimum, and any outliersbeyond three standard deviations. For example, to calculate fold changes(FC) between data sets obtained from young (y) vs. old (o) mice, thefollowing formula was used:${FC} = {{\frac{{SI}_{o} - {SI}_{y}}{{the}\quad {smallest}\quad {of}\quad {either}\quad {SI}_{y\quad}\quad {or}\quad {SI}_{y}} + {1\quad {if}\quad {SI}_{o}}} \geq {{{SI}_{o\quad}{or}} - {1\quad {if}\quad {SI}_{o}}} < {SI}_{y}}$

[0044] Where SI_(o) is the average signal intensity from a gene-specificprobe family from an old mouse and SI_(y) is that from a young mouse.

[0045] Alternatively, if the Q_(factor), a measure of the non-specificfluorescence intensity background, is larger the smallest of eitherSI_(y) or SI_(o), the FC is calculated as:${FC} = \frac{{SI}_{o} - {SI}_{y}}{Q_{factor}}$

[0046] The Q_(factor) is automatically calculated for different regionsof the microarray, and therefore minimizes the calculation of spuriousfold changes. Average of pair-wise comparisons were made between studygroups, each composed of three animals using Excel software. As anexample, each 5-month-old mouse was compared to each 30-month-old mousegenerating a total of nine pair-wise comparisons.

[0047] The murine 19K gene chip allows one to monitor more than 19,000clustered murine EST transcripts selected from the TIGR (The Institutefor Genome Research) database. This database is created by assemblingESTs into virtual transcripts called tentative mouse consensus sequences(Tcs). These sequence contigs are assigned a TC (tentative mouseconsensus) number. Therefore, each TC number represents a uniquetranscript and allows one to check or obtain the sequence from the TIGRmouse gene index.

[0048] 3. Results

[0049] The results of our analysis are shown below in Tables 1-16.Tables 1-4 and 15-16 are the result of the analysis of mousegastrocnemias muscle. Tables 1 and 15 describe aging-related increasesin gene expression, Tables 2 and 16 describe aging-related decrease ingene expression, Table 3 describes caloric restriction relatedincreases, and Table 4 describes caloric restriction related decreasesin gene expression. Tables 5-10 describe results obtained using mousebrain tissue. Table 5 describes aging-related increases in geneexpression in neocortex, Table 6 describes aging-related decreases ingene expression in neocortex, Table 7 describes caloric restrictionrelated increases in gene expression in neocortex, Table 8 describescaloric restriction related decreases in gene expression in neocortex,Table 9 describes aging-related increases in gene expression in thecerebellum, and Table 10 describes aging-related decreases in geneexpression in the cerebellum.

[0050] Tables 11-14 are the result of the analysis of mouse heartmuscle. Tables 11 and 12, obtained by use of the Mu19K Gene Chip,disclose up-regulated and down-regulated aging-related genes. Tables 13and 14, obtained from the Mu6500 Gene Chip, disclose up-regulated anddown-regulated aging-related genes. TABLE 1 Aging-related increases ingene expression in gastrocnemius muscle of C57BL/6 mice* Δ Age CR ORF(fold) Gene Class/Function Reversal AA106112 3.8 MitochondrialSarcomeric Creatine Energy Metabolism/ATP generation C Kinase AA0717773.8 Synaptic Vesicle Protein 2 Growth Factor/Neunte extension 51% Y000943.6 Ypt 1/ras-related GTP Binding Transport/Protein trafficking CProtein W10855 3.5 Methyl CpG Binding Protein DNA metabolism/genesilencing C W08057 3.5 Heat Shock 27 kDa Protein StressResponse/Chaperone C M17790 3.5 Serum Amyloid A Isoform 4 StressResponse/Unknown N L06444 3.5 GDF-9 Growth Factor/Unknown 50% AA1145763.4 Heat Shock 71 kDa Protein Stress Response Chaperone C W84988 3.3Transcription Regulatory Protein Transcriptional Factor/Unknown N SWI3X64587 3.2 U2AF RNA Metabolism/Splicing Factor C D87902 3.2 ARF5Transport/ADP-nbosylation 87% U19118 3.0 LRG-21 TranscriptionalFactor/Macrophage activation 42% AA068057 2.9 RabB SignalTransduction/Unknown C U05837 2.9 Beta-HexosaminidaseCatabolism/Lysosomal enzyme C W85446 2.8 Protein Kinase C Inhibitor 1Signal Transduction/Unknown 74% Homolog AA060167 2.8 Pre-B CellEnhancing Factor Growth Factor/Cytokine C Precursor M37760 2.7 Serine-2Ultrahigh Sulfur Protein Unknown 45% AA096992 2.7 G25K GTP-BindingProtein Signal Transduction/Unknown N AA008255 2.7 Adaptin Complex SmallChain Unknown 37% Homolog AA166502 2.6 EIF-4A-II RNA Metabolism/RNAhelicase N X66602 2.6 POU-domain protein Transcriptional Factor/UnknownN X79828 2.6 NK 10 Transcriptional Factor/Unknown N V00719 2.6Alpha-Amylase-1 Energy Metabolism/Starch metabolism N L28177 2.6 GADD45Stress Response/Chaperone checkpoint 77% W50941 2.5 NucleotidePyrophosphatase Unknown N X53257 2.5 Neurotrophin-3 GrowthFactor/Reinnervation of muscle 50% M74570 2.4 Aldehyde Dehydrogenase IIStress Response/Aldehyde detoxification 29% D49473 2.4 Sox17Transcriptional Factor/Unknown 86% AA117284 2.3 Zinc Finger Protein 43(HTF6) Transcriptional Factor/Unknown N W63835 2.3 Beta-centractinStructural/Contractility 60% AA089097 2.2 Phosphatidylcholine-transferTransport/Lipid turnover C Protein AA059662 2.2 Protease Do PrecursorStress Response Protease C L22482 2.2 HIC-5 Stress Response Senescenceand differentiation C X78197 2.2 AP-2 Beta TranscriptionalFactor/Neurogenesis N AA059664 2.2 IGF Binding Protein GrowthFactor/Cellular senescence C V00714 2.2 Alpha GlobinStructural/Hemoglobin component C X99963 2.2 rhoB StressResponse/Unknown 87% AA014024 2.1 Dynactin Transport/Neuronal transport55% X65627 2.1 TNZ2 Stress Response/RNA Metabolism 64% X95503 2.1GTP-Binding Protein (IRG-47) Signal Transduction/Unknown 85% V00727 2.1FBJ-MuSV Provirus/None C X12807 2.1 pp2.5 Unknown C W08049 2.1 MAGPStructural/Microfibnl glycoprotein N AA066425 2.1 CO-029 Structural/Cellsurface glycoprotein N W82998 2.1 POLYA + RNA Export Protein RNAMetabolism/RNA export 44% X89749 2.1 mTGIF TranscriptionalFactor/Neuronal differentiation C L07918 2.1 GDP-Dissociation InhibitorTransport/membrane dynamics N X63190 2.1 PEA3 TranscriptionalFactor/Response to muscle injury C

[0051] TABLE 2 Aging-related decreases in gene expression ingastrocnemius muscle of C57BL/6 mice* Δ Age CR ORF (fold) GeneClass/Functlon Reversal D29016 −6.4 Squalene SynthaseBiosynthesis/Cholesterol/fatty acid 52% synthesis AA106126 −4.9 MyosinHeavy Chain, Perinatal Structural Protein/Muscle contraction C D31898−4.4 Protein Tyrosine Phosphatase, Signal Transduction/Unknown 79%PTPBR7 U29762 −4.3 Albumin Gene D-Box Binding TranscriptionalFactor/Albumin synthesis 85% Protein AA061310 −4.1 Mitochondrial LONProtease Energy Metabolism/Mitochondrial biogenesis C AA162443 −3.6Protein Phosphatase PP2a Signal Transduction/Unknown C M89797 −3.5 Wnt-4Signal Transduction/Unknown 72% M16465 −3.4 Calpactin I Light ChainSignal Transduction/Calcium effector C X74134 −3.2 OvalbuminTranscription Factor I Transcriptional Factor/Unknown N U08020 −3.2Alpha 1 Type 1 Collagen Structural Protein/Extracellular matrix N X58251−3.1 Pro-alpha-2(l) Collagen Structural Protein/Extracellular matrix NAA138226 −3.1 Clathrin Light Chain B Intracellular Transport/Vesicletransport C X85214 −3.0 Ox40 Signal Transduction/T Cell activation 50%D76440 −2.9 Necdin Growth Factor/neuronal growth 47% suppressor AA107752−2.9 EF-1-Gamma Protein Metabolism/Protein synthesis 63% W55037 −2.9Alpha Enolase Energy Metabolism/Glycolysis 68% X74134 −2.8 COUP-TFITranscription Factor/Unknown 28% U06146 −2.8 Desintegrin-related ProteinUnknown 28% U39545 −2.8 BMP8b Growth Factor/Unknown C X75014 −2.7 Phox2Homeodomain Protein Transcriptional Factor/Neuronal 65% differentiationand survival U22031 −2.6 20S Proteasome Subunit ProteinMetabolism/Protein turnover 44% U70210 −2.5 TR2L TranscriptionalFactor/Apoptosis modulator N X76652 −2.5 3f8 Structural Protein/Neuronaladhesion N W54288 −2.5 PKCSH Signal Transduction/Unknown C M81475 −2.5Phosphoprotein Phosphatase Energy Metabolism/Glycogen metabolism CU22394 −2.3 mSin3 Transcriptional Factor/Inhibitor of 46% cellproliferation M83336 −2.3 gp130 Signal Transduction/Unknown 77% L34611−2.3 PTHR Signal Transduction/Ca homeostasis N X52046 −2.3 Pro-Alpha1(III) Collagen Structural Protein//Extracellular matrix N L2450 −2.2 DNABinding-protein Unknown 58% AA103356 −2.2 Calmodulin SignalTransduction/Calcium effector N L37092 −2.2 p130PITSL Cyclin-kinase DNAMetabolism/Cell cycle control N AA061604 −2.2 Ubiquitin ThiolesteraseProtein Metobolism/Protein turnover C AA139680 −2.2 DNA Polymerase AlphaPrimase DNA Metabolism/DNA replication N AA034842 −2.1 ERV1 DNAMetabolism/Maintenance of MtDNA 46% M21285 −2.1 Stearoyl-CoA DesaturaseBiosynthesis/ synthesis C U11274 −2.1 PmuAUF1-3 RNA Metabolism/RNAdegradation N U73744 −2.1 HSP70 Stress Response/Chaperone N J03398 −2.1MDR Membrane Protein/Unknown N AA145829 −2.1 26S Proteasome ComponentTBP1 Protein Metabolism/Protein turnover C M32240 −2.1 GAS3 GrowthFactor/Apoptosis and growth arrest 55% L00681 −2.1 Unp UbiquitinSpecific Protease Protein Metabolism/Protein turnover N U34277 −2.0 PAFAcelylhydrolase Unknown N U35741 −2.0 Rhodanese ProteinMetabolism/Mitochondrial C protein folding W53731 −2.0 SignalRecognition Particle Intracellular Transport/Protein trafficking CReceptor AA044497 −2.0 Zinc Finger Protein 32 TranscriptionalFactor/Unknown 40% L27842 −2.0 PMP35 Energy Metabolism/Poroxisomeassembly 60% AA106406 −2.0 ATP Synthase A Chain Energy Metobolism/ATPsynthesis N AA041826 −2.0 IPP-2 Energy Metabolism/Glycogen Metabolism C

[0052] TABLE 3 Caloric restriction-related increases in gene expressionΔ CR ORF (fold) Gene Class/Function U68267 9.6 Myosin Binding Protein HStructural/Myofibnl interactions (MyBP-H) X13135 4.7 Fatty Acid SynthaseBiosynthesis/Fatty acid synthesis U05809 4.5 LAF1 Transketolase EnergyMetabolism/Carbohydrate metabolism W53351 4.1 Fructose-bisphosphateEnergy Metabolism/Glycolysis Aldotase M15501 3.5 Cardiac Muscle AlphaActin Structural/Muscle contraction AA071776 3.5 Glucose-6-PhosphateEnergy Metabolism/Glycolysis Isomerase AA073283 3.3 Cardiac MuscleMyosin Beta-Actin Structural/Contractile protein AA138226 2.9 ClathrinLight Chain B Transport/Axonal transport L42115 2.9 Insulin-ActivatedAmino Acid Transport/Aminoacid transport Transporter U37222 2.8Adipocyte Complement- Growth Factor/Unknown Related Protein (Acrp30)W89939 2.7 FK506-Binding Protein Signal Transduction/Neuronal (FKBP-12)regeneration X16314 2.5 Glutamine Synthetase Biosynthesis/Glutaminesynthesis AA080277 2.5 Sodium Potassium ATPase Membrane Protein/Ion pumpAlpha-2 Chain W30250 2.5 Myosin Light Chain 1 Structural/Contractileprotein AA137659 2.4 Cytochrome P450-IIC12 Biosynthesis/Steroidbiosynthesis AA031112 2.4 ZFP-37 Transcriptional Factor/Unknown U342952.3 Glucose Dependent Energy Metabolism/Insulin sensitizerInsulinotropic Polypeptide W54288 2.3 Protein Kinase-C Substrate SignalTransduction/AGE receptor (80K-H) U01841 2.3 Peroxisome ProliferatorEnergy Metabolism/Insulin sensitizer Receptor Gamma (PPAR) AA109527 2.3Actin 1 Structural/Contractile protein AA145829 2.3 26S Protease SubunitTBP-1 Protein Metabolism/26S proteasome component Y00137 2.3Lymphotoxin-Beta Signal Transduction/Cytokine AA107752 2.2 ElongationFactor 1-gamma Protein Metabolism/Protein synthesis AA016431 2.2Keratinocyte Lipid-binding Unknown/Fatty acid binding Protein M93275 2.1Adipose Differentiation Unknown Related Protein (ADFP) W53731 2.1 SignalRecognition Particle Protein Metabolism/Protein synthesis Receptor AlphaSubunit U60328 2.1 Proteasome Activator PA28 Protein Metabolism/Proteinturnover Alpha Subunit W78478 2.1 Gamma E-crystallin Unknown X67083 2.1Chop-10 (gadd153) Stress-Response/Growth arrest U40189 2.1 NeuropeptideY Unknown AA020281 2.1 Progesterone Reductase Metabolic/Progesteronemetabolism AA022083 2.0 Huntingtin Unknown X59990 2.0 mCyP-S1(Cyclophilin) Protein Metabolism/Protein folding X56548 2.0 PurineNucleoside Biosynthesis/Purine turnover Phosphorylase L28116 2.0 PPARDelta Energy Metabolism/Peroxisome induction U43319 2.0 Frizzled 6Unknown X14432 2.0 Thrombomodulin Unknown L32973 2.0 Thymidylate KinaseBiosynthesis/dTTP sythesis D76440 1.9 Necdin Growth Factor/Neuronalgrowth suppressor L36860 1.9 GCAP Signal Transduction/Calcium-bindingregulatory protein W08293 1.9 Translocon-Associated ProteinMetabolism/Protein Protein Delta translocation AA041826 1.9 ProteinPhosphatase Energy Metabolism/Inhibition Inhibitor 2 (IPP-2) of glycogensynthesis D42083 1.9 Fructose 1.6-bisphosphatase EnergyMetabolism/Gluconeogenesis AA008737 1.9 Peroxisomal Protein PAS8Transport/Peroxisome targeting W57495 1.8 60S Ribosomal Protein L23Protein Metabolism/Protein synthesis D83585 1.8 Proteasome Z SubunitProtein Metabolism/Protein turnover M13366 1.8 Glycerophosphate EnergyMetabolism/Electron Dehydrogenase transport to mitochondna U37091 1.8Carbonic Anhydrase IV Energy Metabolism/CO₂ disposal

[0053] TABLE 4 Caloric restriction-related decreases in gene expressionΔ DR ORF (fold) Gene Class/Function AA062328 −3.4 DnaJ Homolog 2 StressResponse/Chaperone X03690 −2.5 Ig Heavy Chain Constant ImmuneFunction/Antibody Region mu(b) U60453 −2.3 Ezh1 (Zeste Homolog 2)Transcriptional Factor/Gene silencing M83380 −2.3 relB TranscriptionalFactor/Unknown D38613 −2.1 921-L Presynaptic Protein Unknown X82457 −2.0es64 Unknown U35646 −2.0 Aminopeptidase Protein Metabolism/Proteinturnover W13412 −1.9 ATP Synthase Coupling Energy Metabolism/ATPsynthesis Factor B M92416 −1.9 FGF-6 Growth Factor/Muscle regenerationU58497 −1.9 mp86 (Mnb Protein Kinase) Signal Transduction/Unknown L29454−1.9 Fbn-1 (Fibrillin) Structural/Microfibnl organization U56773 −1.9Pelle-like Protein Kinase Signal Transduction/Unknown D49439 −1.9 TFIIDSubunit p80 Transcriptional Factor/Unknown D31943 −1.9 InducibleSH2-Containing Growth Factor/Cytokine Protein U47737 −1.9 TSA-1 SignalTransduction/T cell function X63023 −1.9 Cytochrome P-450-IIIA StressResponse/Detoxification X53476 −1.8 HMG-14 DNA Metabolism/Chromalinremodeling L33768 −1.8 JAK3 Signal Transduction/T cell function U03283−1.8 Cyp 1b1 Cytochrome P450 Stress Response/Detoxification U14390 −1.8Aldehyde Dehydrogenase-3 Stress Response/Detoxification U75530 −1.8PHAS-II Protein Metabolism/Translation inhibitor X13605 −1.8 HistoneH3.3 DNA metabolism/Chromatin remodeling U65313 −1.8 G3BP DNAmetabolism/Helicase AA062349 −1.8 P31 Protein Metabolism/Proteinturnover X76850 −1.8 MAPKAP2 Stress Response/Unknown D43694 −1.8 Math-1Transcription Factor/Neuronal differentiation U66887 −1.8 RAD50 DNAMetabolism/DNA repair M83219 −1.8 MRP14 Growth Factor/InflammationZ14986 −1.8 SAMDC Biosynthesis/Polyamine synthesis W17516 −1.8 NEDD8Unknown D78641 −1.7 Membrane Glycoprotein Unknown D26123 −1.7 CarbonylReductase Unknown U71205 −1.7 nt Signal Transduction/Unknown U31510 −1.7ADP-ribosyltransferase Protein Metabolism/ADP-ribosylation L4406 −1.7Hsp 105-beta Stress Response/Chaperone AA059718 −1.7 DNA Polymerase BetaDNA Metabolism/DNA repair D16464 −1.7 HES-1 TranscriptionFactor/Neuronal differentiation D87963 −1.7 ETFR-1 TranscriptionalFactor/Unknown U12236 −1.7 Alpha M290 Integrin Signal Transduction/Celland matrix adhesion X98848 −1.7 6-phosphofructo-2-kinase EnergyMetabolism/glycolysis W41974 −1.7 ATP-Dependent RNA RNAMetabolism/Unknown Helicase-Homolog X75285 −1.6 Fibulin-2Structural/Basement membrane M96265 −1.6 GALT EnergyMetabolism/Glycolysis D67015 −1.6 97kDa Nuclear Pore Transport/Nuclearimport Targeting Complex AA002750 −1.6 5-lypoxygenase ActivatingBiosynthesis/Leukotriene synthesis Protein (FLAP) X93357 −1.6 SYTTranscriptional Factor/Unknown W13191 −1.6 Thyroid Hormone ReceptorMetabolic/Thyroid hormone receptor Alpha-2 U43206 −1.6Phosphatidylethanolamine Signal Transduction/Unknown Binding ProteinW11169 −1.6 SUI1ISO1 Protein Metabolism/Translation initiation factorW42234 −1.6 XPE DNA Metabolism/DNA repair W08897 −1.6 Seryl-tRNASynthetase Protein Metabolism/Protein synthesis AA027739 −1.6Heterogeneous Nuclear Transcriptional Factor/Unknown Ribonucleoprotein K

[0054] TABLE 5 Aging-related increases in gene expression in neocortexof C57BL/6 mice* Δ Age Signal Intensity CR ORF (fold) SE old Young GeneClass Prevention M88354 5.7 1.9 165 −109 Vasopressin-neurophysin IIOsmotic stress  68% M17440 4.9 0.2 786 141 Complement C4Immune/inflammatory  52% AA120109 4.1 0.8 278 65 Interferon-inducedprotein 6-16 homolog Immune/inflammatory 100% M88355 2.7 0.6 195 70Oxytocin-neurophysin Osmotic stress  23% AA037945 2.5 0.2 254 73Beta-SNAP homolog Transport N AA162093 2.5 0.2 145 21 Pre-mRNA splicingfactor PRP22 RNA metabolism N AA137962 2.4 0.2 150 39 RAS-relatedprotein RAB-14 Neurotransmitter release N K01347 2.3 0.4 420 178 Glialfibrillary acidic protein (GFAP) Stress response  38% AA027404 2.3 0.1129 −43 Na/K-transporting ATPase beta-2 chain Ionic transport N U605932.3 0.4 279 131 Cap43 Stress response N AA137871 2.3 0.6 55 −35Phosphatidylinositol-4-phosphate 5-kinase Signal transduction N U617512.3 0.2 299 128 VAMP-1 Transport N M21050 2.2 0.2 209 74 Lysozyme CImmune/inflammatory  54% AA153990 2.2 0.9 343 155 GTP: AMPphosphotransferase Energy metabolism 100% mitochondrial W29462 2.1 0.3114 −49 Calpactin I light chain Structural N L39123 2.1 0.2 1887 768Apolipoprotein D (apoD) Stress response N U16297 2.0 0.5 124 47Cytochrome B561 Transport N M26251 2.0 0.3 484 260 Vimentin Stressresponse N AA163911 2.0 0.2 130 38 Casein kinase I, delta isoform Stressresponse N AA022006 2.0 0.2 115 −48 CD40L receptor precursorImmune/inflammatory N AA124859 2.0 0.2 17 −54 ICAM-2 Immune/inflammatoryN Y00305 1.9 0.2 225 101 Potassium channel protein-1 Transport NAA116604 1.9 0.1 515 272 Cathepsin Z Stress response  70% M95200 1.9 0.3168 92 Vascular endothelial growth factor Growth factor N L16894 1.9 0.4123 −71 Cyclophilin C-AP Stress response 100% L20315 1.9 0.2 120 66 MPS1gene Immune/inflammatory N AA028501 1.9 0.2 74 16 Cytochrome c oxidasesubunit VIII-H Energy metabolism N X86569 1.9 0.2 24 −31 LIM-kinaseUnknown N AA105716 1.9 0.2 107 14 Fructose-1,6-bisphosphatase homologEnergy metabolism  87% W13646 1.8 0.1 1278 705 Ti-225 (ubiqurtin) Stressresponse N J03236 1.8 0.3 681 362 JunB Stress response  46% X52886 1.80.1 1050 555 Cathepsin D Stress response  64% AA028273 1.8 0.3 331 153Protein phosphatase inhibitor 2 (IPP-2) Unknown N X16995 1.8 0.1 757 375N10 Steroid metabolism N X16995 1.8 0.1 624 363 Complement C1q B-chainImmune/inflammatory 100% X66295 1.8 0.1 823 467 Complement C1q C-chainImmune/inflammatory  75% U22445 1.8 0.5 201 160 Serine/threonine kinase(Akt2) Energy metabolism 100% U17297 1.8 0.2 6 −43 Integral membranephosphoprotein 7.2b Unknown N AA059700 1.8 0.2 1467 797 MHC class IB(2)-microglobulin Immune/inflammatory  64% L29503 1.8 0.1 192 103Myelin/oligodendrocyte glycoprotein (Omg) Unknown N AA168918 1.8 0.4 326166 Na/K-transporting ATPase gamma chain Transport N M90364 1.8 0.1 326202 Beta-caterun Stress response N AA061086 1.8 0.2 179 89 Hsp40 Stressresponse  52% W50891 1.8 0.3 41 −3 Creatine kinase Energy metabolism NW67046 1.8 0.2 105 71 Exodus-2 Immune/inflammatory N W13875 1.8 0.2 216125 Myosin regulatory light chain 2-A Unknown N X67083 1.8 0.3 121 47Chop-10 GADD153 Stress esponse N AA089110 1.8 0.2 23 −35 Dynein betachain, ciliary Transport N V00727 1.7 0.3 404 236 c-fos(p55) Stressresponse 100% AA062328 1.7 0.2 113 23 DNAJ protein homolog 2 Stressresponse N AA122619 1.7 0.3 14 −43 Set protein (HLA-DR associatedprotein II) Unknown N M73741 1.7 0.2 1313 730 Alpha-B2-crystallin geneStress response  67% X70393 1.7 0.4 146 65 Inter-alpha-inhibitor H3chain lmmune/inflammatory  56% AA124698 1.7 0.7 100 42 Lethal(1)discslarge-1 Unknown N W14434 1.7 0.2 401 240 Fructose-bisphosphate aldolaseEnergy metabolism N W89579 1.7 0.2 83 −3 RAS-related protein RAB-4Signal transduction N AA089333 1.7 0.1 336 221 Cathepsin S precursorStress response  56% U19521 1.7 0.2 70 31 Vesicle transport protein(munc-18c) Transport N AA107137 1.7 0.3 204 118 Casein kinase 1, gammaUnknown N AA106166 1.7 0.2 2312 1372 Elongation factor 2(EF-2) homologRNA metabolism N M31811 1.7 0.1 748 457 Clathrin light chain B Transport100% AA140487 1.7 0.3 23 −25 Cyclophilin A homolog Stress response 100%U37419 1.7 0.2 58 −29 G protein alpha subunit (GNA-15) Signaltransduction N AA114781 1.7 0.2 52 26 Uridylate kinase DNA metabolism NX58861 1.6 0.1 1128 694 Complement C1Q alpha-chain Immune/inflammatory100% AA048650 1.6 0.2 169 100 Estradiol 17 B-dehydrogenase 3 homologSteroid metabolism N W46723 1.6 0.2 83 46 Creatine kinase, B chainhomolog Energy metabolism N U16162 1.6 0.7 112 82 Prolyl 4-hydroxylasealpha(1)-subunit Structural N X68273 1.6 0.2 105 73 MacrosialinImmune-inflammatory N W48962 1.6 0.7 87 38 B-adrenergic receptor kinase1 Signal transduction N AA063858 1.6 0.2 135 80 RHO-related GTP-bindingprotein RHOG Signal transduction 100% M15525 1.6 0.1 22 −58 Laminin B1Neuronal outgrowth N AA068780 1.6 0.1 275 187 Phosphoserineaminotransferase homolog Unknown  76% U27462 1.6 0.3 133 79 BS4 peptideUnknown N AA106077 1.6 0.1 116 64 Glutathione peroxidase Stress response 76% AA119959 1.6 0.2 194 128 Protein transport protein SEC23 TransportN AA061170 1.6 0.2 39 −18 NEDD-4 protein Unknown N X16151 1.6 0.2 93 61T-lymphocyte activation 1 protein (ETa-1) Immune/inflammatory N W294621.6 0.3 114 −49 Calpactin I light chain (p11) Unknown N AA097579 1.6 0.124 −20 Zinc finger protein 91 homolog Unknown  52% X64070 1.6 0.3 252163 46kDa marinose 6-phosphate receptor Lysosomal N W48519 1.6 0.2 98100 GRP94 homolog Stress response N X78682 1.6 0.2 408 269 B-cellreceptor associated protein (BAP) 32 Unknown N AA106166 1.6 0.2 23121372 Elongation factor 2 homolog Protein metabolism N AA169054 1.6 0.2279 184 GTP-binding protein GTR1 Signal transduction N W51181 1.6 0.3 4225 DNA-directed RNA polymerase II RNA metabolism  75% AA036390 1.6 0.2146 83 DNA-binding protein inhibitor ID-1 Transcriptional factor  75%L08115 1.5 0.2 309 236 Human CD9 antigen homolog Structural 100% U373531.5 0.2 191 121 Protein phosphatase 2A B'alpha3 Signal transduction Nregulatory subunit L10244 1.5 0.2 316 206 Spermidine/spermineN1-acetyltransferase Polyamine metabolism N J05154 1.5 0.2 72 6Cholesterol acyltransferase (LCAT) Steroid metabolism N D43643 1.5 0.262 36 YL-1 Unknown N M34141 1.5 0.1 39 5 COX-1 lmmune/inflammatory 100%L28177 1.5 0.1 35 −9 GADD 45 Stress response N X85992 1.5 0.1 51 10Semaphorin C Neuronal remodelling N AA098307 1.5 0.2 85 47 Tubulin beta5 Microtubule component N

[0055] TABLE 6 Aging-related increases in gene expression in neocortexof C57BL/6 mice* Δ Age Signal Intensity CR ORF (fold) SE old Young GeneClass Prevention X74134 −3.0 1.1 157 387 Ovalbumin upstream promoterTranscriptional factor N L24430 −2.7 0.6 56 161 Osteocalcin precursorUnknown N AA124352 −2.5 0.5 19 274 Neuromedin B precursor homologNeurotransmission  54% D31898 −2.2 0.5 116 253 Protein tyrosinephosphatase. PTPBR7 Unknown N W29468 −2.2 0.3 133 284 Myosin light chain2 mRNA Unknown N AA065993 −2.2 0.3 16 115 GTP-binding nuclear proteinRAN homolog Signal transduction N U35323 −2.1 0.3 11 135 H2-M Unknown NW98695 −2.1 0.2 3 120 Plasma retinol-binding protein precursor Steroidmetabolism N AA062463 −2.1 0.2 63 168 Kidney androgen-regulated proteinSteroid metabolism N U38196 −2.1 0.6 64 151 Palmytoylated protein p55Signal transduction 100% L36135 −2.1 0.3 −42 32 T cell receptor deltachain, C region Immune/inflammatory N D32200 −2.1 0.3 38 101 Hes-3Unknown N W98898 −2.1 0.4 −21 125 Transforming protein RFP Growth factorN U29762 −2.0 0.2 396 744 Albumin gene D-Box binding protein Circadianrhythm N AA138711 −2.0 0.5 222 321 Protein kinase C inhibitor proteinUnknown N W13586 −2.0 0.3 135 548 Atnal/fetal isoform myosin alkalilight chain Structural  49% X67812 −2.0 0.3 41 120 ret proto-oncogeneUnknown N M97812 −2.0 0.2 12 85 REX-1 Steroid metabolism N W11011 −2.00.4 418 673 NEDD8 Protein metabolism N X13538 −2.0 0.2 66 176 Hox-1 4gene Growth factor N X66405 −2.0 0.5 186 330 Collagen alpha 1 chain typeVI Structural 100% AA050791 −2.0 0.5 194 355 Creatine kinase, M chainEnergy metabolism N W55515 −1.9 0.4 132 243 Cyclic-AMP-dependent ATF-4Transcriptional factor 100% L33416 −1.9 0.3 184 291 Clone p85 secretedprotein Unknown 100% X70398 −1.9 0.9 186 325 PTZ-17 Growth factor NM84412 −1.8 0.1 46 128 Antigen (Ly-9) Immune/inflammatory  47% AA067927−1.8 0.2 63 132 DNA-PK-catalytic subunit DNA metabolism N Y09585 −1.80.4 143 212 Serotonin 4L receptor Neurotransmission N X95255 −1.8 0.1 672 Gli3 protein Growth factor N U37459 −1.8 0.1 37 87 Glial-derivedneurotrophic factor (GDNF) Growth factor N M99377 −1.8 0.3 121 270Alpha-2 adrenergic receptor Neurotransmission N D83585 −1.8 0.5 916 1457Proteasome Z subunit Protein metabolism N U52222 −1.8 0.2 61 160 Mel-1amelatonin receptor Neuropeptide N M13710 −1.7 0.3 120 219 Interferonalpha-7 gene Immune/inflammatory N D76446 −1.7 0.2 103 199 TAK1 Stressresponse N U64445 −1.7 0.2 12 56 Ubiquitin fusion-degradation protein(ufd1l) Protein metabolism 100% U39545 −1.7 0.3 144 235 Bonemorphogenetic protein 8B (Bmp8b) Growth factor N W59776 −1.7 0.2 95 174Vacuolar ATP synthase catalytic subunit A pH regulation N AA071792 −1.70.2 36 89 GSTP-1 Protein metabolism N AA052547 −1.7 0.3 −2 95 PA-FABPhomolog Unknown 100% D63819 −1.7 0.2 61 143 Neuropeptide Y-YII receptorNeuropeptide N W08326 −1.7 0.2 173 265 51PK(L) homolog Unknown NAA000468 −1.7 0.2 113 195 p55CDC DNA metabolism 100% U66203 −1.7 0.2 111181 FHF-3 Growth factor N AA051632 −1.7 0.2 112 167 MEK5 Signaltransduction  61% AA051147 −1.7 0.2 114 264 Chemotaxis protein cheYhomolog Unknown N X84692 −1.7 0.2 24 91 Spnr mRNA for RNA bindingprotein RNA metabolism N U53925 −1.7 0.3 100 169 HCF1 Unknown  33%AA038142 −1.7 0.3 251 376 RCC1 DNA metabolism N W54682 −1.7 0.1 87 188Antithrombin-III precursor (ATIII) lmmune/inflammatory N U13705 −1.7 0.2324 494 Plama glutathione peroxidase (MUSPGPX) Stress response  44%X75384 −1.7 0.2 91 158 SAX-1 Growth factor N Z32767 −1.7 0.3 117 205RAD52 DNA metabolism  76% AA107752 −1.6 0.6 225 336 Elongation factor1-gamma Protein metabolism N M12836 −1.6 0.6 56 116 T-cell receptorgamma chain gene C-region lmmune/inflammatory N AA060704 −1.6 0.2 9751407 Glutathione S-transferase MU 5 Unknown N AA118294 −1.6 0.1 99 161Vitronectin homolog Unknown N AA123026 −1.6 0.1 72 166Pancreatitis-associated protein 3 homolog Unknown 100% AA065652 −1.6 0.139 99 Ubiquitin carboxyl-terminal hydrolase Protein metabolism N W46104−1.6 0.2 19 58 DNA-repair protein XP-E DNA metabolism N M88694 −1.6 0.267 109 Thioether S-methyltransferase Unknown  57% AA117004 −1.6 0.1 6 61Heat shock cognate 71 KD protein homolog Stress response N M15501 −1.60.1 229 325 Adult cardiac muscle alpha-actin Structural 100% U49430 −1.60.2 78 108 Ceruloplasmin Transport N X69019 −1.6 0.2 36 71 Hox 3.5 gene.complete cds Growth factor N M28666 −1.6 0.2 317 496 Porphobilinogendeaminase Biosynthesis  44% W368759 −1.6 0.1 49 112CMP-N-acetylneuraminate-beta-1,4- Sialyltransferase N galactosidealpha-2,3-sialyltransferase W11666 −1.6 0.2 105 207 apolipoprotein HLipid metabolism N W09925 −1.6 0.1 26 102 Endothelial actin-bindingprotein Growth factor  74% AA116282 −1.6 0.1 140 355 TNF alpha precursorImmune/inflammatory  56% D37791 −1.6 0.0 556 895Beta-1,4,-galactosyltransferase Unknown N W12658 −1.6 0.2 143 216FKBP-rapamycin associated protein (FRAP) Unknown N Z468454 −1.6 0.2 −1639 Preproglucagon Energy metabolism N AA103045 −1.5 0.1 57 106 Cleavagestimulation factor. 64 Kd subunit RNA metabolism N AA108891 −1.5 0.2 462 Putative ATP-dependent RNA helicase RNA metabolism  55% AA153522 −1.50.3 80 159 Serine/threonine protein kinase sulu Unknown N M23501 −1.50.2 33 101 TCA3 Unknown  61% AA063762 −1.5 0.1 112 193 Zinc fingerprotein 36 homolog (KOX18) Unknown  63% AA098588 −1.5 0.1 84 137 Zincfinger protein HRX (ALL-1) Unknown  57% W15873 −1.5 0.2 161 258 tctex-1mRNA Unknown  61% AA170748 −1.5 0.1 −14 48 40S Ribosomal protein S4Unknown N W80326 −1.5 0.1 −11 86 Sex-determining protein FEM-1 Unknown NAA140159 −1.5 0.2 65 134 Thiol-specific antioxidant protein homologStress response N D16492 −1.5 0.1 19 58 RaRF Unknown  56% D85845 −1.50.2 48 88 Atonal homolog-3 Growth factor N L06451 −1.5 0.1 −55 87 Agoutiswitch protein mRNA Unknown 100% AA166500 −1.5 0.2 51 141Transcriptional regulatory protein RPD3 Unknown N L28035 −1.5 0.1 377578 Protein kinase C-gamma mRNA Unknown 100% U52197 −1.4 0.1 296 439Poly(A) polymerase V RNA metabolism N D29763 −1.4 0.1 799 1130Seizure-related, product 6 type 3 precursor Unknown/response  50% U22015−1.4 0.1 89 130 Retinoid X receptor interacting protein Steroidmetabolism 100%

[0056] TABLE 7 Caloric restriction-related increases in gene expressionin neocortex of C57BL/6 mice* CR Signal Intensity ORF Increase SE CRControl Gene Class J04971 4.1 0.7 410 87 Slow/cardiac troponin C (cTnC)Unknown D13903 3.1 1.2 150 49 MPTPdelta (type A) Growth factor M366603.1 0.3 24 −114 NAD(P)H menadione oxidoreductase Stress response M556173.1 0.6 27 −48 MMCP-4 unknown W65178 3.0 0.3 39 −35 BMP-1 Growth factorAA118682 3.0 0.6 62 −12 Trithorax homolog 2 Transcriptional factorAA014816 3.0 0.7 257 38 Prolactin homolog Unknown U39904 2.9 1.4 100−169 Citron, putative rho/rac effector Signal transduction AA061310 2.90.7 87 29 Mitochondnal LON protease Energy metabolism U02098 2.8 0.5 8236 Pur-alpha DNA metabolism M29395 2.8 0.3 38 −20Orotidine-5-monophosphate decarboxylase DNA metabolism M23236 2.8 0.5 16−57 Retrovirus POL protein homolog Unknown M13019 2.8 0.4 −15 −130Thymidylate synthase DNA metabolism X76858 2.6 0.4 58 −17 phi AP3Unknown W56940 2.5 0.2 81 24 Neuronal-glial cell adhesion moleculehomolog Unknown X59846 2.4 0.6 215 156 GAS 6 Growth factor U05247 2.40.3 666 250 c-Src kinase Signal transduction AA104316 2.3 0.3 25 −46Type-I ER resident kinase PERK Stress response L04302 2.3 0.2 49 2Thrombospondin 3 Structural W55507 2.3 0.3 31 −14 D(2) Dopamine receptorNeurotransmission AA014909 2.3 0.4 56 −39 Gastrula zinc finger proteinXLCGF20.1 Unknown U46923 2.2 0.8 71 −13 G protein-coupled receptor GPR19Unknown M34857 2.2 0.1 176 57 Hox-2.5 Growth factor M74227 2.2 0.3 16248 Cyclophilin C (cyp C) Immune/inflammatory W12794 2.2 0.3 48 −59Transforming protein MAF homolog Transcriptional factor X62940 2.2 0.12199 931 TSC-22 Unknown L06451 2.2 0.1 136 −55 Agouti switch proteinUnknown AA052547 2.2 0.1 74 −2 Fatty acid-binding protein, epidermal(E-FABP) Transport W17956 2.2 0.4 108 −2 Zinc finger protein 42 homologUnknown X95226 2.2 0.4 53 −1 Dystrobrevin Structural AA152808 2.2 0.2141 24 Proteine kinase PASK Signal transduction AA014512 2.1 0.5 32 −3Unknown Unknown W74811 2.1 0.4 17 −46 Apolipoprotein c-II precursor(APO-CII) Transport U69270 2.1 0.7 323 210 LIM domain binding protein 1(Ldb1) Growth factor W54720 2.1 0.2 100 19 Ca**-transporting ATPase(brain isoform 1) Unknown X13460 2.1 0.1 313 151 Annexin VI Signaltransduction U61362 2.1 0.3 57 −35 Groucho-related gene 1 protein(Grg 1) Unknown W09323 2.1 0.3 91 −11 Endothelin-2 precursor (ET-2)Unknown W70403 2.1 0.2 17 −19 mafF Unknown AA071685 2.0 0.4 93 47Elongation factor 1-alpha chain homolog Protein metabolism W14673 2.00.4 133 8 BAT3 Unknown W53409 2.0 0.3 33 −28 Protein kinase C homolog,alpha type Signal transduction U19880 2.0 0.1 28 −6 D4 dopamine receptorgene Neurotransmission M75875 2.0 0.4 280 119 MHC H2-K homolog UnknownW62842 2.0 0.2 12 −24 ATP synthase lipid-binding protein P2 precursorEnergy metabolism U48397 2.0 0.3 126 40 Aquaponn 4 Osmotic stress J004752.0 0.3 74 −34 Ig alpha chain region C Immune/inflammatory M57960 2.00.2 21 −18 Carboxylesterase Unknown X57800 2.0 0.1 560 274 PCNA DNAmetabolism U36277 2.0 0.3 123 70 I-kappa B alpha chain Stress responseAA015291 2.0 0.3 140 67 Probable E1-E2 ATPase unknown W82109 2.0 0.3 7329 Kinesin light chain (KLC) Transport M83380 1.9 0.2 25 −26 RelBImmune/inflammatory U13174 1.9 0.2 36 2 Basolateral Na-K-2Clcotransporter Transport M33960 1.9 0.2 19 1 Plasminogen activatorinhibitor (PAI-1) Growth factor X72310 1.9 0.3 106 38 DRTF-polypeptide-1(DP-1) Transcriptional factor AA059886 1.9 0.2 8 −52 Retinaldegeneration C protein Apoptotic factor U02278 1.9 0.2 18 −32 Hox-B3Growth factor AA072842 1.9 0.2 126 72 Na*- and Cl-dependent transporterNTT73 Transport M98339 1.9 0.2 113 −15 GATA-4 Transcriptional factorW13427 1.9 0.3 195 94 Platelet factor 4 precursor Unknown U44955 1.9 0.245 2 Alpha3 connexin gene Transport L24191 1.9 0.1 104 25 Intrinsicfactor Transport W08109 1.9 0.3 142 99 Protein kinase C inhibitor 1(PKCl-1) homolog Unknown W36570 1.9 0.3 146 67 DNA mismatch repairprotein MSH2 DNA metabolism Z34524 1.8 0.2 42 −20 Protein kinase DSignal transduction AA105081 1.8 0.2 46 −1 Initiation factor IF-2,mitochondrial Protein metabolism U18797 1.8 0.2 95 −3 MHC class Iantigen H-2M3 Unknown M11988 1.8 0.3 141 82 Hox-A6 Growth factor U179611.8 0.2 123 81 p62 ras-GAP associated phosphoprotein Signal transductionW85103 1.8 0.1 24 −17 IGF binding protein 4 precursor homolog Energymetabolism X07997 1.8 0.2 230 128 MHC class I T-cell antigen Lyt3.1Immune/inflammatory W46723 1.8 0.3 164 83 Creatine kinase, B chainhomolog Unknown W48464 1.8 0.4 18 −7 Protein-tyrosine phosphatase MEG2homolog Unknown L06322 1.8 0.1 84 −4 Delta opioid receptorNeurotransmission W49178 1.8 0.1 605 508 Tubulin beta-1 chain homologStructural W48477 1.8 0.2 106 61 Thyrotroph embryonic factor homologUnknown W64225 1.8 0.3 80 44 G21 Unknown L28167 1.8 0.2 88 45 Zincfinger protein Unknown W97199 1.8 0.3 37 62 Negative regulator oftranscription subunit 2 Transcriptional factor X01971 1.8 0.2 20 −35Interferon alpha 5 (Mu IFN-alpha 5) Immune/inflammatory AA061266 1.8 0.3164 125 Oxysterol-binding protein homolog Transport U21855 1.8 0.3 94 31CAF1 Transcriptional factor W87078 1.8 0.1 182 90 Unknown Unknown W346871.8 0.3 188 105 Actin alpha skeletal muscle homolog Structural K012381.8 0.3 191 127 Interferon alpha 2 Immune/inflammatory U15635 1.8 0.2 709 IFN-gamma induced (Mg11) Unknown L13968 1.8 0.1 98 26 UCR-motifDNA-binding protein Transcriptional factor M86567 1.8 0.2 122 60 GABA-Areceptor alpha-2 subunit Neurotransmission M87861 1.8 0.3 51 −22 Granulemembrane protein 140 Structural W55350 1.8 0.3 14 −4Phosphatidylinositol transfer protein B isoform Unknown L43567 1.8 0.135 −21 B-cell receptor gene lmmune/inflammatory AA153196 1.8 0.2 55 −19Ubiqurlin-activating enzyme E1 homolog Protein metabolism M28312 1.8 0.1109 41 Metalloprotease inhibitor TIMP1 Immune/inflammatory

[0057] TABLE 8 Caloric restriction-related decreases in gene expressionin neocortex of C57BL/6 mice* CR De- Signal Intensity ORF crease SE CRControl Gene Class X76505 −7.2 1.0 −195 73 Tyro 10 Signal transductionU43088 −6.3 1.1 −109 164 IL-17 (CTLA-8) Immune/inflammatory W50186 −5.62.1 −38 129 Heavy chain homolog Unknown Y07711 −3.5 0.5 28 151 ZyxinSignal transduction Z47205 −3.1 0.8 45 200 PLZF Transcriptional factorAA000203 −2.8 0.7 −93 26 Corticosteroid-binding globulin precursorTransport W83658 −2.6 0.5 51 197 Guanine nucleotide-binding proteinSignal transduction G(I)/G(S)/G(O) homolog L46815 −2.6 0.2 8 67 Ig kappachain recombination and transcription DNA metabolism enhancer AA153484−2.4 0.5 208 456 SERCA2 Ion transport W51466 −2.4 0.4 12 147 Chlorinechannel protein P64 homolog Unknown U27398 −2.4 0.4 39 132 XPC DNAMetabolism X58069 −2.2 0.7 54 164 H2A.X DNA metabolism U50712 −2.2 0.454 156 MCP-5 Immune/inflammatory M61909 −2.1 0.3 39 125 NF-kappa-B p65Stress response AA072643 −2.1 0.4 49 110 Midkine precursor homologStress response L01991 −2.1 0.3 48 132 PANG Unknown L04678 −2.1 0.2 −64138 Integrin beta 4 subunit Structural W64628 −2.1 0.4 62 197 Guaninenucleotide-binding protein Signal transduction G(I)/G(S)/G(O) gamma-7subunit X54098 −2.0 0.3 55 136 lamin B2 Structural AA023458 −2.0 0.3 20107 Heat shock 27 KD protein homolog Stress response D63380 −2.0 0.2 −1932 Alpha-1,3-fucosyltransferase Protein metabolism U15548 −2.0 0.3 −3042 Beta 2 thyroid hormone receptor Energy metabolism AA123385 −2.0 0.257 117 Phosphorylase B kinase gamma catalytic chain Energy metabolismX57349 −2.0 0.4 −10 49 Transferrin receptor Transport D00659 −2.0 0.1 135 Aromatase P450 Biosynthesis AA028875 −2.0 0.2 −32 54 Glycine-richcell wall structural homolog Lysosomal X76291 −2.0 0.1 11 79 Ihh (IndianHedgehog) Signal transduction AA041982 −1.9 0.3 44 84 LARK Circadianregulation AA118758 −1.9 0.2 103 206 Multifunctional aminoacyl-tRNAsynthetase Protein synthesis W75353 −1.9 0.3 90 162 Apolipoprotein C-IVTransport W55410 −1.9 0.2 30 111 Tubulin gamma chain homolog UnknownL20343 −1.9 0.2 22 102 L-type calcium channel beta 2a subunit isoformTransport W91095 −1.9 0.5 44 93 Valyl-tRNA synthetase Protein metabolismX81593 −1.9 0.1 53 119 Winged-helix domain Transcriptional factor M38248−1.9 0.2 −6 25 BALB8N Unknown J04694 −1.8 0.3 48 134 Alpha-1 type IVcollagen Structural L47650 −1.8 0.3 50 85 STAT6 R Immune/inflammatoryAA023595 −1.8 0.1 38 133 Frizzled protein precursor Signal transductionAA015168 −1.8 0.2 42 97 Interferon-gamma receptor beta chain homologImmune/inflammatory AA013951 −1.8 0.1 32 38 Creatine transporter homologEnergy metabolism W78443 −1.8 0.2 17 106 MKP-X Signal transductionD31842 −1.8 0.2 66 126 PTP36 Structural W50138 −1.8 0.2 1 162 Putativeserine/threonine-protein kinase B0464.5 Unknown L35307 −1.8 0.2 33 104c-Krox Transcriptional factor AA073154 −1.8 0.3 31 68 Alpha-caternhomolog Structural W12720 −1.8 0.3 149 251 RAP-2B homolog Signaltransduction AA170169 −1.8 0.2 −17 37 Elongation factor 1-gamma homologProtein metabolism W48951 −1.8 0.3 8 30 Voltage-dependentanion-selective channel Unknown protein 2 homolog M35732 −1.8 0.3 −13 17Seminal vesicle secretory protein IV Unknown AA145515 −1.8 0.3 68 187Pre-MRNA splicing factor PRP6 RNA metabolism W13162 −1.8 0.1 −7 62 Celldivision protein kinase 4 DNA metabolism J03482 −1.8 0.2 42 113 HistoneH1 DNA metabolism W82793 −1.8 0.1 −4 59 Topoisomerase E III homolog DNAmetabolism Z31360 −1.8 0.3 1 51 P/L01 Unknown Y09632 −1.8 0.1 16 37Rabkinesin-6 Transport AA066621 −1.8 0.2 13 63 60S ribosomal protein L10Protein metabolism U67874 −1.8 0.3 46 85 Ubiqurtin thiolesterase familyProtein metabolism AA109714 −1.8 0.3 562 968 SKP1 RNA metabolismAA007957 −1.8 0.2 210 357 Threonyl-tRNA synthetase homolog Proteinmetabolism AA162633 −1.8 0.2 46 95 Isoleucyl-tRNA synthetase Proteinmetabolism M17299 −1.8 0.3 29 101 Phosphoglycerate kinase (pgk-2) Energymetabolism AA050102 −1.7 0.3 211 263 Elongation factor 2 (EF-2) Proteinmetabolism W54637 −1.7 0.2 72 137 Tubulin bets-2 chain class-II homologUnknown D10028 −1.7 0.3 167 312 Glutamate receptor channel subunit zeta1 Neurotransmission M28587 −1.7 0.2 −52 30 Alpha leukocyte interferonImmune/inflammatory AA023506 −1.7 0.2 60 144 Insulin receptorsubstrate-3 Energy metabolism W70629 −1.7 0.3 92 158 COPII Proteinmetabolism U33626 −1.7 0.3 66 125 PML isoform 1 (Pml) Unknown AA144746−1.7 0.2 42 92 EF-1-delta Protein metabolism M19380 −1.7 0.3 1406 2303Calmodulin (Cam III) Signal transduction AA144136 −1.7 0.2 43 100Choline kinase R1 homolog Biosynthesis AA165847 −1.7 0.3 331 509EF-1-alpha2 homolog Protein metabolism W33415 −1.7 0.2 90 136 ATPcitrate-lyase Unknown U35233 −1.6 0.1 71 109 Endothelin-1Vasoconstrictive peptide W57384 −1.9 0.3 6 15 ATP synthase A chainhomolog Energy metabolism X60452 −1.6 0.3 124 200 Cytochrome P-450IIIAStress response AA022127 −1.6 0.1 172 279 Vascular endothelial growthfactor Unknown AA168841 −1.6 0.2 169 289 Serine/threonine-protein kinasePAK Unknown AA120586 −1.6 0.1 9 64 Apolipoprotein B-100 precursor Stressresponse AA104561 −1.6 0.2 104 166 EIF-4A homolog Protein metabolismX17071 −1.6 0.1 25 90 Trophoblast-specific protein Growth factor M96265−1.6 0.1 153 250 Galactose-1-phosphate uridyl transferase BiosynthesisAA145160 −1.6 0.2 178 287 Translational initiation factor 2 alphaProtein metabolism X63473 −1.6 0.1 69 110 m4 muscannic acetylcholinereceptor Neurotransmission AA002750 −1.5 0.2 176 290 5-lipoxygenaseactivating protein (FLAP) Immune/inflammatory W64698 −1.5 0.2 51 63Protein kinase C inhibitor 1 Signal transduction U63841 −1.5 0.1 120 197NeuroD3 Growth factors U04294 −1.5 0.1 99 150 Potassium channel subunit(m-eag) Transport M33227 −1.5 0.2 259 396 Cryptdin-related (CRS4C)Immune/ inflammatory U20532 −1.5 0.1 45 67 P45 NF-E2 related factor 2(Nrf2) Transcriptional factor AA140026 −1.5 0.1 378 519 DNA directed RNApolymerase polypeptide G DNA metabolism W09025 −1.5 0.1 47 68 ATPsynthase B chain homolog Energy metabolism W29163 −1.5 0.1 342 465Leydig cell tumor 10kd protein homolog Unknown AA155191 −1.5 0.1 36 65Kinesin heavy chain Transport M80360 −1.5 0.1 63 96 Rep-3 DNA metabolismAA044561 −1.4 0.2 93 132 PEP carboxykinase - mitochondnal Energymetabolism AA096843 −1.4 0.2 130 175 Unknown Unknown X57277 −1.4 0.1 9081298 Rac 1 Signal transduction W82998 −1.4 0.1 256 363 BUB3 DNAmetabolism

[0058] TABLE 9 Aging-related increases in gene expression in the cereumof C57BL/6 mice* Fold Signal Intensity CR ORF Change SE Old Young GeneClass Prevention AA120109 9.3 3.4 254 29 lnterferon-induced protein 6-16precursor Immune/inflammatory N M21050 6.4 0.9 291 14 Lysozyme P (Lzp-s)Immune  88 X56824 5.7 1.9 160 89 Tumor-induced 32 kD protein (p32)Unknown 100 V00727 5.6 2.6 282 57 c-fos Stress  30 M13019 4.9 0.7 109 3Thymidylale synthase DNA metabolism  87 L16894 4.7 1.0 192 5 CyclophilinC (CyCAP) Immune/inflammatory N AA146437 4.7 0.3 841 169 Cathepsin Sprecursor Stress  62 X58861 4.4 0.2 719 160 C1Q alpha-chainImmune/inflammatory  80 W67046 4.3 0.8 50 1 C6 chemokineImmune/inflammatory N X66295 4.1 0.6 508 147 C1q C-chainImmune/inflammatory  56 W65899 4.1 1.8 152 58 Guanine nucleotide-bindingprotein Signal transduction  80 U00677 4.1 2.2 16 −10 Syntrophin-1Neurotransmission 100 X68273 3.9 1.8 108 −37 MacrosialinImmune/inflammatory N U19854 3.9 0.5 35 −63 Ubiqurtinating enzyme E2-20KProtein metabolism 100 U63133 3.9 1.1 318 95 Emv-3 Viral N L20315 3.80.1 97 26 MPS1 Immune/inflammatory  56 K01347 3.8 0.7 337 109 Glialfibrillary acidic protein (GFAP) Stress  61 M17440 3.7 0.3 445 116Sex-limited protein (SIpA) Immune/inflammatory N X91144 3.6 1.3 38 −2P-selectin glycoprotein ligand 1 Immune/inflammatory 100 U43084 3.5 0.854 18 IFIT-2 Glucocorticoid-attenuated response Immune/inflammatory NAA089333 3.4 0.2 208 61 Cathepsin S precursor Stress  71 X83733 3.4 0.371 −7 SAP62-AMH RNA metabolism 100 W45750 3.3 1.3 197 257 Guaninenucleotide-binding protein G(T) Signal transduction 100 M22531 3.3 0.2431 146 Clq B-chain Immune/inflammatory  65 AA031244 3.1 0.4 83 9 DNAJprotein homolog HSJ1 Stress 100 M60429 3.1 0.8 121 37 Ig-gamma 1 chainImmune/inflammatory 100 AA036067 3.0 0.4 815 311 Apolipoprotein Eprecursor (APO-E) Lipid transport  28 U06119 2.9 0.3 27 4 Cathepsin Hprepropeptide (ctsH) Stress response  55 AA106347 2.9 0.3 243 57Angiotensinogen precursor Osmoregulation  80 W98998 2.9 0.7 182 79Neurogenic locus notch homolog protein 1 Immune/inflammatory  100AA059700 2.8 0.3 2013 687 MHC class I B(2)-microglobulinImmune/inflammatory  45 U73037 2.8 0.8 69 41 Interferon regulatoryfactor 7 (7) Immune/inflammatory  50 Y00964 2.8 0.3 780 316beta-hexosaminidase (Hexb) Unknown  47 X55315 2.8 0.6 63 15 Fetuscerebral cortex for 3UTR Transcription factor 100 U37465 2.8 0.1 15 −7Protein tyrosine phosphatase phi (PTPphi) Unknown  63 L07803 2.7 1.2 24−15 trombospondin 2 Structural N U19119 2.7 0.3 52 −5 G-proiein-likeLRG-47 Immune/inflammatory N X52886 2.6 0.2 893 326 Cathepsin D Stressresponse  38 W70578 2.6 1.2 31 7 Antigen WC1 1 Immune/inflammatory  81X16705 2.6 0.4 93 −4 Laminin B1 Structural  84 W57539 2.6 0.3 28 6Oocyte zinc finger protein XLCOF8 Unknown N X52308 2.6 0.4 32 9 ThrombinFibrinogen activation  91 U70859 2.6 0.7 109 46 Cationic amino acidtransporter (CAT3) AA transport  49 U41497 2.6 1.1 160 40 Very-longchain acyl-CoA dehydrogenase Lipid metabolism 100 AA089339 2.6 0.5 76 31Cystatin C precursor Immune/inflammatory 100 X16151 2.5 0.1 239 95 EarlyT-lymphocyte activation 1 protein Immune/inflammatory  49 U37419 2.5 0.5111 −2 G protein alpha subunit (GNA-15) Unknown N K02785 2.5 0.5 15 −6r-fos Stress response N M12289 2.5 0.5 39 25 Pennatal skeletal myosinheavy chain Structural 100 X58849 2.4 0.4 59 13 Murine Hox-4.7Developmental 100 AA063858 2.4 0.2 89 32 Rho-related GTP-binding proteinRHOG Signal transduction  74 D10632 2.4 0.2 33 −27 Zinc finger proteinTranscription factor N U33005 2.3 0.4 35 −8 tbc1 Unknown N W85160 2.30.7 70 41 40S ribosomal protein S4, X isoform Unknown 100 U57331 2.3 1.042 15 Transcription factor Tbx6 (tbx6) Developmental  92 U44731 2.3 0.271 20 Putative purine nucleotide binding protein Immune/inflammatory NW87253 2.3 0.6 58 16 Integrin beta-5 Subunit precursor Cell adhesion 100U53142 2.3 0.2 223 101 Endothelial constitutive nitric oxide SynthaseNeurotranmission N AA087715 2.3 0.1 85 −6 GTPase-activating proteinSPA-1 Unknown N D49429 2.3 0.3 554 251 Rad21 homolog DNA metabolism  73AA155318 2.3 0.4 291 129 HNRP1 RNA metabolism N AA032593 2.3 0.1 99 17Transducin beta chain 2 Signal transduction  83 X03690 2.3 0.2 45 −13 lgmu chain Immune/inflammatory  93 M26417 2.3 0.5 54 28 T cell receptorbeta chain Immune/inflammatory 100 X86374 2.2 0.6 73 38 TAG7Immune/inflammatory  38 W90894 2.2 0.3 27 −11 Cell division proteinkinase 4 DNA metabolism 100 M84005 2.2 0.7 83 51 Olfactory receptor 15Odor receptor  23 X55573 2.2 0.5 55 19 Brain-derived neurotrophic factorGrowth factor N W30129 2.2 0.3 90 −16 Phosphatidylinositol glycan hmologStructural 100 AA163771 2.2 0.3 153 67 EIF-28 epsilon subunit Proteinmetabolism N X72910 2.1 0.4 96 44 HSA-C Unknown N AA116604 2.1 0.2 303181 Cathepsin Z Stress response  64 L16462 2.1 0.4 51 4 BCL2-relatedprotein A1 Apoptosis  58 L13732 2.1 0.4 53 29 Natl. resistance-asstd.macrophage protein1 Immune/inflammatory  85 D37791 2.1 0.1 934 424Beta-1,4-galactosyltransferase Protein metabolism  82 AA125097 2.0 0.1618 313 Unknown Unknown  94 AA109998 2.0 0.2 40 12 Hexokinase D homologEnergy metabolism 100 M88127 2.0 0.2 33 −8 APC2 homolog Unknown  82X13538 2.0 0.5 114 45 Hox-1,4 Growth/development 100 V01527 2.0 0.5 2810 H2-IA-beta Immune/inflammatory 100 AA144411 2.0 0.1 86 79 UnknownUnknown 100 X63535 2.0 0.1 55 21 Tyrosine-protein kinase receptor UFOSignal transduction N M83348 2.0 0.1 42 22 Pregnancy specificglycoprotein homolog Unknown N W08211 2.0 0.2 62 26 TGF-beta receptortype III Signal transduction 100 W13136 2.0 0.4 266 87 AngiotenisinogenOsmoregulation  36 W46084 2.0 0.1 89 45 Unknown Unknown N U73744 2.0 0.13958 2909 Heat shock 70 Stress response 100 D29763 1.9 0.2 465 271Seizure-related, product 6 type 3 Unknown  47 AA118121 1.9 1.0 51 37lsoleucyl-tRNA synthetase Protein metabolism N M27034 1.9 0.2 258 163MHC class 1 D-region Immune/inflammatory N U35249 1.9 0.1 68 36CDK-activating kinase assembly factor DNA metabolism  61 J03776 1.9 0.437 22 Down regulatory protein (rpt-1r) of IL-2 receptorImmune/inflammatory N U28728 1.9 0.3 221 112 Els Signal transduction  66AA124192 1.9 0.2 411 244 Unknown Unknown  44 W63809 1.8 0.4 136 80Unknown Unknown  73 X16834 1.8 0.2 455 182 Galectin-3Immune/inflammatory N X16995 1.8 0.2 351 221 N10 nuclear hormonalreceptor homolog Unknown 100 J02870 1.8 0.2 848 380 40S ribosomalprotein SA Protein metabolism 100 L21768 1.8 0.2 153 76 EGF15 Growthfactor  68 AA117284 1.8 0.1 217 123 Zinc finger protein homolog UnknownN

[0059] TABLE 10 Aging-related increases in gene expression in the cereumof C57BL/6 mice* Fold Signal Intensity CR ORF Change SE Old Young GeneClass Prevention U00445 −4.3 1.4 39 132 Glucose-6-phosphatase Energymetabolism  79 W48504 −4.1 1.1 32 78 phosphoneuroprotein 14 homolog)Unknown N AA153337 −3.9 0.7 67 218 Myosin regulatory light chain 2(MLC-2). Unknown  61 W51213 −3.9 0.5 14 57 NEDD-4 homolog Proteinmetabolism  55 X56304 −3.1 0.4 2 27 Tenascin Growth/development N W12681−3.1 0.6 30 126 Hepatocyte growth factor Growth/development  37 Z68889−2.9 1.0 30 70 Wnt-2 homolog Growth/development N W55684 −2.8 0.6 13 37Brain protein i47 Unknown N U04827 −2.8 0.5 94 219 Brain fattyacid-binding protein (B-FABP) Growth/development N AA008066 −2.7 1.0 161 Pre-mRNA splicing factor PRP22 Unknown  74 W55300 −2.7 0.7 20 47Fatty acid-binding protein, heart (H-FABP) Unknown  71 D13903 −2.7 0.5 737 MPTPdelta (type A) Growth/development N AA013976 −2.6 0.5 162 405 POLpolyprotein; reverse transcriptase; Unknown N ribonuclease H W10865 −2.60.2 14 142 Myosin light chain 1, atnal/foetal isoform Unknown N AA020296−2.5 0.2 −162 166 NG9 Growth/development 100 W64865 −2.5 1.1 10 31Stat-3 Unknown N AA139694 −2.5 0.3 64 203 Beta-myosin heavy chainTransport 100 U29762 −2.5 0.3 304 657 Albumin gene D-Box binding proteinTranscription Factor N M87276 −2.4 0.5 16 34 Thrombospondin Structural 52 X02677 −2.4 0.2 63 160 Anion exchange protein Anion exchanger 100X04836 −2.4 0.2 22 68 T-cell antigen CD4 Immune/inflammatory 100 X87242−2.4 0.3 48 111 unc-33 Growth/development  70 AA163021 −2.4 0.2 28 143Annexin VIII Signal transduction  84 M31810 −2.4 0.3 29 113 P-proteinmembrane transporter Transport 100 M97900 −2.4 0.6 18 49 Unknown Unknown 20 M15008 −2.4 0.6 101 227 Steroid 21-hydroxylase B Steroid metabolism100 M99377 −2.4 0.5 77 191 Alpha-2 adrenergic receptor NeurotransmissionN M32490 −2.4 0.3 62 122 Cyr61 Growth/development  41 AA168350 −2.3 0.3130 237 Cysteinyl-tRNA synthetase Protein metabolism  83 AA061206 −2.30.2 8 52 Unp (ubiquitin protease) Protein metabolism N W12794 −2.3 0.323 96 Unknown Unknown  78 AA050593 −2.3 0.1 5 69 Unknown Unknown  62AA050715 −2.3 0.3 64 148 Smoothelin Structural  92 AA106463 −2.2 0.3 110277 Phosphoenolpyruvate carboxykinase. Energy metabolism N X90829 −2.20.3 −16 9 Lbx1 Growth/development N X65588 −2.2 0.3 −1 24 mp41Neurotransmission N J00475 −2.2 0.2 −23 58 lg alpha chainImmune/inflammatory N X03019 −2.2 0.3 4 71 GM-CSF Immune/inflammatory 26 W34687 −2.2 0.4 62 115 Alpha-actin Transport  78 W75614 −2.2 0.4 2756 Alpha-synuclein Growth/development N AA068153 −2.2 0.3 14 39Polyadenylate-binding protein RNA metabolism  55 U36842 −2.1 0.5 22 36Riap 3-inhibitor of apoptosis Apoptosis 100 W09127 −2.1 0.3 3 85 60Sribosomal protein L22 Protein metabolism 100 D63819 −2.1 0.2 29 87Neuropeptide Y-Y1 receptor Neurotransmission N M33884 −2.1 0.1 70 139Env polyprotein Viral protein  55 AA144430 −2.1 0.3 64 156 NF-KB P100inhibitory subunit Stress response  48 AA168554 −2.1 0.3 119 246 UnknownUnknown  85 U35730 −2.1 0.8 12 30 Jerky Unknown N M92649 −2.1 0.4 45 112nitric oxide synthase Neurotransmission N D12907 −2.1 0.2 55 126 Serineprotease inhibitor homologue Unknown  85 M17327 −2.1 0.2 234 566 Envpolyprotein Viral protein  56 AA170444 −2.1 0.2 172 246Ubiquitin-activating enzyme E1 Protein metabolism 100 W12658 −2.1 0.3203 415 FKBP-rapamycin associated protein Unknown N AA123026 −2.1 0.3 60116 REG 2 Unknown 100 W13125 −2.1 0.5 111 232 Phenylalanyl-tRNAsynthetase beta chain Protein metabolism N AA103862 −2.1 0.4 53 143Unknown Unknown N U21301 −2.1 0.6 30 62 c-mer tyrosine kinase receptorSignal transduction N W13586 −2.1 0.1 29 136 Myosin light chain 1homolog Transport 100 W42217 −2.1 0.1 69 143 Ribosomal protein S20Protein metabolism 100 AA153522 −2.1 0.4 95 191 Serine/threonine kinaseSignal transduction  78 W30612 −2.0 0.1 70 160 Chloride intracellularchannel 3 Transport 100 W11621 −2.0 0.4 78 138 Zinc finger protein 126Unknown N X72805 −2.0 0.3 25 63 CD-1 histone H1t DNA metabolism N L08407−2.0 0.3 38 117 Collagen type XVII Structural N AA145609 −2.0 0.2 55 134cAMP responsive element modifier Transcriptional factor  34 W12756 −2.00.1 48 117 Unknown Unknown  92 W75523 −2.0 0.3 48 95 Vertebrate homologof C. elegans Lin-7 type 2 Unknown N D85904 −1.9 0.3 69 129 Heat shock70-related protein Apg-2 Stress response N AA138911 −1.8 0.2 176 311 RNAhelicase PRP16 RNA metabolism 100 W42216 −1.8 0.1 183 361 SWI/SNFrelated homolog Transcriptional factor  74 W12395 −1.8 0.4 141 237Transcription elongation factor A (SII) Transcriptional factor  88K03235 −1.8 0.1 84 149 Prolifenn 2 Growth factor 100 AA145859 −1.8 0.14110 5250 Unknown Unknown 100 W57194 −1.8 0.2 61 108 Ubiquitin carboxylterminal hydrolase 12 Protein metabolism N AA166440 −1.7 0.1 229 389Phosphatidylserine decarboxylase Protein metabolism N L33726 −1.7 0.1 69128 Fascin homolog 1 Structural 100 L35549 −1.7 0.4 30 38 Y-box bindingprotein homolog Unknown 100 AA154514 −1.7 0.1 7639 12878 ATP synthase Achain (protein 6) homolog Energy metabolism 100 AA143937 −1.7 0.1 384697 Beta-centractin Transport  70 AA027387 −1.7 0.1 169 270 Rab-4BTransport  51 L38971 −1.7 0.2 205 334 Integral membrane protein 2Unknown  43 W10526 −1.7 0.1 193 301 Ca** channel, voltage-dep., gammasubunit 1 Transport  90 W12204 −1.6 0.2 114 200Ca2+/calmodulin-dependent protein kinase Signal transduction N isoformgamma B AA170173 −1.6 0.1 149 289 NTT-73 Transport 100 M64403 −1.6 0.1126 208 Cyclin D1 homolog DNA metabolism 100 W13191 −1.6 0.1 288 347Thyroid hormone receptor alpha 2 Energy metabolism  87 U47543 −1.6 0.1121 205 NGF1-A binding protein 2 (NAB2) Growth factor N D70848 −1.6 0.2154 246 Zic2 (cerebellar zinc finger protein) Neural development  77X56518 −1.6 0.3 106 164 Acetylcholinesterase Neurotransmission NAA144588 −1.6 0.2 233 368 Beta-adrenergic receptor kinase 2 homologNeurotransmission  33 AA139828 −1.6 0.1 224 351 gonadotropin inducibletranscription repressor-1 Unknown 100 homolog AA061170 −1.6 0.2 43 65WW-domain oxidoreductase homolog Unknown N X58287 −1.6 0.3 84 153mR-PTPu Signal transduction N L13129 −1.6 0.1 162 220 Annexin A7Exocytosis  90 D85037 −1.6 0.1 50 77 Doc2beta Neruotransmission N U30823−1.6 0.2 55 102 Myocyte enhancer factor-2A Transcriptional factor  33W64791 −1.6 0.1 92 143 Galactokinase Energy metabolism N X52622 −1.6 0.1274 377 IN Viral protein 100 AA063914 −1.5 0.1 175 267 Alpha-tubulinTransport 64

[0060] TABLE 11 Genes upregulated by aging in C57BL/6 mice heart fromMu19K GeneChip Fold Probe Set oc1 oc2 oc3 yc1 yc2 yc3 Change TC27774 396218 490 −1328 −2197 −1280 25.8 TC35932 71 1391 355 −596 −507 −1500 17.2TC39719 938 595 1380 529 −129 −562 14.6 TC24697 1510 2431 3697 173 −823−537 13.9 TC17809 4141 4286 4415 224 369 921 11.0 TC28794 1358 1313 1445349 −38 657 10.4 TC16257 439 867 471 −121 −528 166 10.3 TC34515 16871117 966 465 −1068 −1737 9.4 TC29214 102 154 188 −381 −122 −209 9.0TC32857 733 915 524 200 82 90 8.3 TC37114 553 803 466 377 −99 59 8.2TC17940 947 1889 1474 −54 160 −1487 8.1 TC39890 912 1658 1190 639 617 87.7 TC39498 1080 738 1754 −29 634 −462 7.3 TC25820 340 510 325 −353 −315−575 6.1 TC24908 12482 8941 7330 1337 1838 1387 5.8 TC29305 1271 1020827 841 382 606 5.5 TC16024 739 1570 995 603 312 123 4.8 TC33899 304 287240 64 30 73 4.8 TC16184 1294 3064 3523 428 388 447 4.7 TC39399 338 421286 −81 208 27 4.5 TC17839 1506 946 2315 248 512 146 4.5 TC18386 18221967 1585 281 566 477 4.4 TC27769 3796 5647 3986 1260 975 2286 4.4TC37583 433 617 758 119 425 93 4.3 TC22269 6795 7593 8793 920 2322 52054.1 TC28239 2039 1359 881 227 495 604 4.1 TC34440 340 310 258 21 −437−170 4.1 TC39301 803 1692 1539 27 710 778 4.1 TC29662 997 2372 1701 174650 694 4.0 TC33757 339 323 257 49 76 231 3.9 TC29977 858 631 879 102541 335 3.9 TC19997 419 358 384 84 67 266 3.8 TC27675 4002 5625 66931292 1580 1426 3.8 TC21921 677 779 864 339 43 229 3.8 TC41800 915 4411157 −8 69 180 3.7 TC31694 2158 2467 2245 449 306 976 3.7 TC28855 282194 355 67 127 62 3.6 TC31277 311 243 445 44 182 172 3.6 TC21628 176 422304 124 76 68 3.5 TC36063 498 623 390 −80 346 −52 3.5 TC33608 514 449479 140 165 124 3.4 TC38147 420 212 473 61 173 211 3.3 TC23622 112 328186 −55 60 99 3.2 TC34697 549 450 752 89 356 370 3.2 TC22213 1892 23052099 655 730 644 3.1 TC31569 282 113 247 73 127 4 3.1 TC28942 517 10551020 301 364 224 3.0

[0061] TABLE 12 Genes downregulated by aging in C57BL/6 mice heart fromMu19K GeneChip Fold Probe Set oc1 oc2 oc3 yc1 yc2 yc3 Change TC27282 20−2020 −2141 5078 970 879 −86.2 TC32064 −217 −844 −511 2335 2211 2176−58.6 TC24160 −1155 −3091 −2382 427 4103 4674 −56.2 TC14603 867 −2795−2128 4729 2680 2255 −53.4 TC22507 −1155 −1599 −1409 1319 2177 2942−50.4 TC15929 −1203 −1586 −1787 1348 1014 2026 −47.0 TC19943 −687 −669−428 2880 2552 1067 −41.7 TC18736 −1142 787 −1647 2711 3654 4006 −33.0TC19957 1242 −501 958 6796 6771 5343 −30.5 TC37452 175 −1172 −441 8202013 1233 −27.3 TC33452 532 −740 −465 2021 880 719 −26.3 TC14870 −289−1650 −2496 30 209 1249 −25.2 TC26312 −118 −73 −146 406 1251 1344 −24.3TC25802 −688 −736 −1968 31 707 695 −23.7 TC14624 −227 −943 −758 1675 718352 −22.6 TC41568 −684 −3089 −1954 7 711 129 −22.6 TC16488 −1548 −57−1609 1055 1739 190 −22.5 TC18539 122 1114 −269 3415 2604 2614 −21.6TC37617 −1738 −296 −2150 2156 2231 422 −20.6 TC39618 −56 −204 −168 7691196 887 −19.5 TC37350 −1070 −657 −655 1944 1258 260 −19.5 TC36639 1496−3251 −23 4489 2756 6211 −19.4 TC16420 48 −674 −17 1059 1053 1072 −18.6TC37529 177 151 333 6190 3159 2499 −18.3 TC15736 −67 −1109 −1133 242 530647 −18.2 TC36992 498 −2096 −450 2140 2451 1214 −17.9 TC28761 326 −105847 4047 2990 1712 −17.9 TC25360 −1421 −2210 −2177 332 173 204 −17.2TC16633 −66 −612 −638 626 240 496 −17.0 TC18250 145 −416 −464 2429 890804 −16.3 TC35586 −337 −526 6 762 782 328 −16.2 TC37067 2006 137 25897334 6130 5348 −16.0 TC40509 176 −216 197 2219 724 1177 −15.9 TC37745380 −1137 141 822 1566 1043 −15.8 TC24220 648 227 48 1916 1805 2138−14.9 TC17700 159 −80 −657 565 810 690 −14.4 TC17256 −2800 −3715 −3550629 2754 950 −13.4 TC37672 −117 427 247 1149 1712 1737 −13.0 TC18637 202−208 −312 1012 907 794 −12.8 TC15863 −639 250 289 882 794 1198 −12.7TC23647 −575 334 −1428 1821 2149 2101 −12.5 TC16841 375 −198 430 11771044 1257 −12.3 TC27576 −70 75 428 596 1326 857 −12.2 TC21963 −281 −437−368 944 136 231 −12.2 TC36608 −527 −316 −140 343 254 7 −12.1 TC26887 60188 −100 589 933 734 −11.9 TC24501 539 518 79 4279 1947 1811 −11.8TC36239 902 −102 843 1587 1899 2152 −11.3 TC38050 −47 −81 115 324 633645 −11.3 TC37660 −1 −617 −203 450 240 314 −11.1 TC34986 −1 −98 −28 726315 235 −10.7 TC30885 402 −55 27 878 734 398 −10.4 TC16723 478 276 621703 1736 1138 −10.3 TC20671 −70 −827 −303 948 1087 410 −10.2 TC14753−332 −265 −325 418 335 276 −10.1 TC16229 −156 515 107 1224 681 1077−10.1 TC24641 −372 −382 −329 127 845 718 −10.0 TC35052 139 −86 −19 504459 447 −9.9 TC20554 158 392 625 1255 896 1199 −9.8 TC25572 −470 −460−871 472 1340 791 −9.5 TC21262 220 −336 1193 2061 1581 2928 −9.5 TC2541648 −285 −104 487 554 460 −9.5 TC41297 373 −176 455 1093 976 991 −9.4TC37701 −219 −338 −398 830 294 236 −9.4 TC34944 364 462 369 3507 32713393 −9.3 TC31449 −7 53 −51 300 252 217 −9.0 TC41997 167 −142 199 6821057 893 −8.8 TC36033 −164 −295 −678 1048 194 241 −8.8 TC27468 584 492560 1011 1031 929 −8.8 TC16039 603 −2181 −1612 2105 1544 1004 −8.6TC19352 −918 −290 −600 1103 700 859 −8.5 TC25041 229 −697 −295 726 515558 −8.4 TC35104 548 1 563 1294 1692 715 −8.3 TC25357 143 −277 −40 897788 1407 −8.0 TC22194 119 −63 −176 477 440 633 −7.9 TC20469 284 −303−850 1031 591 674 −7.7 TC41078 −35 −289 42 551 232 148 −7.7 TC39603 417−253 300 813 952 586 −7.6 TC36846 64 −83 117 606 487 353 −7.2 TC24619−11 −273 −224 212 483 418 −7.1 TC15831 1167 1269 87 3253 1942 1814 −7.1TC25629 −4 −309 −341 387 106 167 −7.1 TC23144 −91 −175 −322 770 114 393−7.0 TC29553 77 −27 −110 93 283 185 −7.0 TC36286 −312 −574 −44 702 929668 −6.8 TC23964 1265 1225 276 6611 4409 5007 −6.8 TC37675 19 103 139408 734 469 −6.6 TC41144 236 58 273 1095 734 708 −6.6 TC40883 −31 −25188 201 473 370 −6.6 TC27606 −640 −765 −579 232 208 394 −6.5 TC14712 1140643 −15 1661 1331 2644 −6.5 TC26859 803 95 985 3249 2325 2184 −6.4TC33246 168 −216 −384 517 283 384 −6.4 TC37343 180 −27 34 459 508 346−6.3 TC37275 1193 720 808 1722 1828 1992 −6.3 TC18134 685 695 488 145 5796 −6.2 TC40210 166 −245 91 354 502 400 −6.1 TC17241 438 −110 756 17502691 2519 −6.1 TC21038 133 −138 −206 600 218 168 −6.1 TC22355 12 −396−116 182 232 177 −6.1 TC38075 111 −40 11 533 588 613 −6.0 TC38184 −263−107 58 293 235 92 −6.0 TC37491 239 166 349 1404 1500 1141 −5.9 TC33420−132 −208 −114 388 128 88 −5.9 TC37318 1331 188 833 1241 3321 2861 −5.8TC37916 −273 −62 −202 198 55 43 −5.8 TC17885 −178 169 −288 1591 14721445 −5.7 TC15884 390 −134 −109 734 431 493 −5.6 TC40452 −94 −141 107291 339 359 −5.6 TC29330 512 370 140 2164 1174 930 −5.6 TC17616 101 4657 531 853 808 −5.6 TC21414 −62 −2 −143 111 296 344 −5.5 TC17717 36 −83−144 222 172 209 −5.4 TC31495 156 155 77 280 502 371 −5.3 TC18144 2048819 1400 3236 3117 3190 −5.3 TC19650 −120 −282 −56 358 86 18 −5.2TC25815 36 224 90 490 506 508 −5.2 TC37544 470 242 458 527 767 691 −5.1TC38870 119 −35 187 1057 704 587 −5.1 TC26789 111 49 −68 240 243 270−5.0 TC37493 103 250 396 993 982 795 −5.0 TC41579 465 120 253 959 557669 −5.0 TC17620 326 452 303 721 565 788 −4.9 TC18572 29 −130 −51 208264 348 −4.9 TC41021 217 84 43 611 329 306 −4.9 TC25021 61 95 69 471 440235 −4.9 TC37829 −235 −243 92 142 292 771 −4.7 TC19783 35 −10 249 371604 767 −4.6 TC24373 −111 −424 171 376 384 395 −4.6 TC41191 54 −407 −30741 36 721 −4.6 TC30942 281 146 19 1772 1068 1025 −4.5 TC14554 28 −14744 651 479 471 −4.5 TC32618 210 68 260 435 504 448 −4.5 TC35574 1063 2951619 2598 3642 3046 −4.5 TC39584 1090 1014 538 2430 3908 4185 −4.4TC37290 −26 −15 90 541 212 211 −4.3 TC14567 968 216 267 2605 1842 1044−4.2 TC30986 66 −14 76 306 151 178 −4.2 TC35356 211 −3 224 474 598 338−4.2 TC35554 91 −100 89 572 566 558 −4.2 TC22851 810 416 520 3098 17731661 −4.2 TC20860 316 118 498 1291 739 695 −4.1 TC41573 212 88 343 6561162 931 −4.1 TC32333 471 489 542 2274 1696 1350 −4.1 TC20845 164 222−12 508 438 361 −4.0 TC37484 192 −14 236 408 384 494 −4.0 TC33993 −342−140 −253 161 567 752 −4.0 TC37769 670 107 485 2676 1219 1617 −3.9TC31667 435 73 167 1141 556 585 −3.9 TC18679 1123 1055 1090 638 626 366−3.9 TC21666 5 81 −153 203 351 195 −3.8 TC41350 213 83 206 680 403 479−3.8 T021304 −109 −65 −63 243 38 61 −3.7 TC39507 −137 −208 −77 310 61 22−3.7 TC19129 827 722 469 1364 1364 1142 −3.6 TC21197 −376 −1186 −10541746 1222 416 −3.6 TC38888 67 8 50 292 106 199 −3.6 TC32452 992 974 11652411 2887 2965 −3.5 TC14511 739 660 298 942 1924 2211 −3.5 TC29246 716546 538 1125 991 1222 −3.4 TC15902 137 −4 55 350 211 209 −3.4 TC37774378 234 424 1148 1146 952 −3.3 TC27288 377 394 816 1451 1663 1554 −3.3TC31668 −76 −153 −46 170 103 10 −3.3 TC41983 252 −1 190 240 490 429 −3.3TC14823 933 420 557 1168 2494 1983 −3.3 TC40714 416 939 354 1914 17441041 −3.3 TC20259 272 22 86 330 285 513 −3.3 TC23344 462 577 862 16022043 2131 −3.3 TC27282 1068 765 508 3300 1911 1689 −3.2 TC21501 500 1332782 4505 3307 3468 −3.2 TC34693 −14 177 761 1242 1088 1137 −3.2 TC41186231 120 272 1122 579 641 −3.1 TC26140 276 −43 141 279 541 452 −3.1TC20981 −59 −53 −38 137 67 86 −3.1 TC39851 97 −176 80 457 204 169 −3.0TC26095 283 532 336 1142 776 909 −3.0 TC16932 125 188 91 490 284 323−3.0 TC22052 100 118 149 375 356 323 −3.0

[0062] TABLE 13 Genes upregulated by aging in C57BL/6 mice heart fromMu6500 GeneChip ORF oc1 oc2 oc3 yc1 yc2 yc3 Fold Change X60103 242 223238 13 −52 65 11.8 AA117446 273 512 453 155 118 66 6.8 M21829 82 83 14124 45 52 5.4 L07297 69 103 101 −52 −30 −43 5.1 X94998 208 168 223 −8 −3580 5.1 W36875 149 126 153 15 64 64 4.9 U00677 171 108 187 18 77 5 4.3M17440 311 354 372 90 84 61 4.0 U08210 45 24 38 −10 4 −17 3.9 AA097087326 628 684 140 181 143 3.5 X62622 180 134 235 81 112 27 3.5 U25844 702607 584 186 204 191 3.3 D13664 218 202 130 40 75 75 3.3 U00674 55 48 15−9 11 15 3.3 Z31663 0 63 55 −42 −100 −88 3.2 X91824 155 121 140 58 60 693.2 AA152695 38 42 26 8 8 14 3.2 AA014024 111 219 218 110 59 72 3.1D16497 1888 1428 3023 664 996 517 3.1 AA036050 52 52 49 18 9 9 3.1L41154 408 305 476 128 152 157 3.1 AA168633 585 654 733 167 253 246 3.1L20276 1761 1059 1201 260 600 829 3.0

[0063] TABLE 14 Genes downregulated by aging in C57BL/6 mice heart fromMu6500 GeneChip ORF oc4 oc5 oc6 yc1 yc2 yc3 Fold Change X54149 52 16 −69106 139 84 −6.2 X98475 −7 37 38 202 136 79 −6.1 U25114 185 133 69 326301 283 −5.4 U58885 −16 33 105 315 212 301 −5.3 X85169 −1 −32 −75 48 4311 −5.0 AA028728 68 −19 17 90 99 116 −4.9 D14336 100 17 26 141 202 176−4.8 W29790 72 91 13 259 196 195 −4.8 L11163 181 334 −18 401 820 512−4.5 AA068712 18 −12 −15 61 69 70 −4.5 D43643 26 −12 −58 69 61 45 −4.3Y08361 35 1 −35 88 54 84 −4.2 W57425 −6 −31 −61 36 9 13 −4.2 L17076 130103 97 645 491 431 −4.1 U08215 45 27 −1 160 74 73 −3.8 AA068780 28 −5−34 86 32 64 −3.8 AA072334 66 43 88 194 160 136 −3.7 AA060808 98 30 57226 159 155 −3.7 W84060 15 36 6 56 91 63 −3.7 X97796 16 5 −24 72 53 37−3.6 X60831 49 35 7 52 59 84 −3.6 AA003162 152 28 108 274 204 224 −3.6W08293 174 130 106 508 356 342 −3.5 AA107999 47 6 −18 77 72 56 −3.5Z47205 112 93 21 127 181 253 −3.3 AA107137 46 −19 −31 87 165 125 −3.2U70017 34 0 3 126 63 48 −3.2 W34891 0 19 19 41 40 36 −3.2 M90364 141 94103 394 273 326 −3.1 W20652 26 43 38 75 63 84 −3.1 W10926 48 −1 −5 99 3482 −3.1 X53532 13 14 15 92 36 57 −3.0 W77701 167 90 68 369 347 251 −3.0U53455 22 29 24 127 62 85 −3.0 U09218 17 22 2 57 71 29 −3.0 D78141 29 245 54 74 65 −3.0

[0064] TABLE 15 Genes upregulated by aging in C57BL/6 mice gastrocnemiusfrom Mu19K GeneChip Probe Set oc1 oc2 oc3 yc1 yc2 yc3 Fold ChangeTC22507 1496 5100 4680 −861 −868 2232 12.3 TC41260 2271 2776 1202 345337 214 7.1 TC15427 3952 6832 4863 392 2541 1658 6.2 TC17528 309 830 202−401 −87 58 4.8 TC39719 467 1194 956 −96 −68 639 4.6 TC30023 3484 15572722 −471 784 −100 4.2 TC15105 2869 2887 744 424 221 −401 4.2 TC228149874 12120 6784 1463 3030 4227 4.2 TC32898 3770 1780 2282 1470 299 5984.0 TC17624 932 1910 1154 96 704 295 3.9 TC38243 3651 2564 2668 22271427 370 3.3 TC32537 2652 2455 3025 723 614 1165 3.3 TC16833 1263 1056635 427 417 −26 3.1 TC37853 655 965 895 237 151 275 3.1 TC35747 768 11981174 477 809 145 3.0 TC36248 3727 6677 4613 2357 2860 1045 2.9 TC168092167 1306 1781 648 1219 566 2.8 TC37410 1198 1044 612 564 545 38 2.8TC29110 1462 775 696 −808 −441 −1038 2.7 TC41340 615 744 603 435 182 4032.7 TC20762 1280 839 1046 582 553 149 2.7 TC41486 2628 3390 2900 7542234 1251 2.7 TC30327 3780 2597 2167 628 1606 1354 2.6 TC41030 402 383450 125 −70 −187 2.6 TC37927 1283 1988 419 −684 −704 −690 2.5 TC35232206 291 846 −414 −154 −217 2.5 TC40552 676 624 566 180 272 −14 2.5TC35879 761 606 643 217 248 316 2.5 TC36106 553 81 381 35 −28 −309 2.4TC14958 431 569 687 37 86 338 2.4 TC15563 1782 2034 1615 779 1031 4232.4 TC37009 5627 4674 6716 3156 3535 2177 2.4 TC38613 14275 16183 146996963 8380 4717 2.4 TC17122 5461 6072 4547 2524 2633 1687 2.4 TC2776944054 58886 54326 31194 27436 14076 2.4 TC33822 6543 3341 4435 1353 27372536 2.4 TC20391 102 324 227 −201 −286 −15 2.4 TC38653 687 826 298 24459 122 2.4 TC40473 533 539 263 57 118 124 2.3 TC17622 1714 1541 1071 926397 609 2.3 TC18112 756 793 703 610 211 251 2.3 TC19062 2563 4000 23911565 2019 1229 2.3 TC16585 4312 3985 4720 2520 2316 1346 2.3 TC37317 7261068 673 494 398 258 2.3 TC40165 817 869 775 448 588 182 2.2 TC217141174 1390 1120 808 475 702 2.2 TC17422 31965 35070 40903 13173 1947714605 2.2 TC37018 592 437 367 217 172 79 2.2 TC16885 2486 2538 923 −830765 −522 2.2 TC34291 13707 19389 10341 8383 5255 6989 2.2 TC37463 14441417 1078 922 520 513 2.2 TC24549 8515 9554 5391 4618 4038 3446 2.2TC35324 321 607 357 140 137 156 2.1 TC31058 1436 1266 1773 514 303 1592.1 TC15920 2072 2001 1360 477 1197 809 2.1 TC29793 1532 1993 2224 4581173 801 2.1 TC37926 2769 2562 1750 865 1108 1169 2.1 TC40454 1344 24802437 590 1123 786 2.1 TC17515 3386 4354 3900 2340 2892 1179 2.1 TC358192072 2558 2188 1248 1174 959 2.1 TC39079 1639 1879 1394 538 1352 726 2.1TC35125 1031 714 880 300 652 40 2.0 TC40951 11 565 108 −204 −192 −5302.0 TC37262 680 922 706 269 530 3 2.0 TC31287 2040 2088 2058 336 12321246 2.0 TC40137 334 303 464 69 135 144 2.0 TC31251 1652 1328 1412 654696 592 2.0 TC31522 6212 5990 6621 3005 3336 4224 2.0 TC37833 1464 1782872 587 766 423 2.0 TC23026 462 265 318 105 88 74 2.0 TC33710 5381 40055984 1782 3214 2638 2.0 TC14237 978 1638 1423 877 412 747 2.0 TC320462438 2103 1415 898 512 1318 2.0 TC15245 2305 2606 4096 1771 1589 503 2.0TC30375 15067 24645 27999 11194 14149 9870 2.0 TC24289 383 454 679 143283 −134 2.0 TC30683 1269 622 565 −320 97 122 2.0

[0065] TABLE 16 Genes downregulated by aging in C57BL/6 micegastrocnemius from Mu19K GeneChip Probe Set oc1 oc2 oc3 yc1 yc2 yc3 FoldChange TC39172 282 384 1189 1388 1492 1767 −8.6 TC24050 −1117 −243 252388 1315 2392 −6.8 TC34953 3835 5266 6073 35656 21430 31766 −6.3 TC343061324 565 −353 1427 2241 3278 −5.6 TC26537 3726 2008 378 6454 4146 9861−5.2 TC35355 245 −492 187 765 951 1217 −4.9 TC40742 −394 229 395 12811132 1041 −4.7 TC24501 152 253 −108 981 536 1084 −4.6 TC14421 419 1398344 2366 1833 2615 −4.5 TC21687 −959 88 1433 2686 2066 2732 −4.5 TC25229369 −201 79 1383 638 1283 −4.2 TC34953 379 2950 2267 5359 3465 5921 −3.9TC24344 473 528 359 1189 1506 2141 −3.7 TC33957 4504 2776 5281 1219714665 15262 −3.6 TC40061 4693 1355 4866 7669 10158 7310 −3.5 TC36858 −65113 276 904 449 854 −3.3 TC15621 3342 3801 2088 5802 5651 7667 −3.1TC22866 2973 2064 3961 6385 9965 9570 −3.1 TC36347 1077 2585 1662 42876166 4493 −3.0 TC26944 13744 8497 7171 26871 31183 24244 −3.0 TC36854−679 139 −105 2255 4600 2220 −2.9 TC32868 −194 501 −963 1491 1485 569−2.9 TC33934 −2432 4016 2471 8604 6093 6420 −2.9 TC34857 819 360 −1652160 2933 3161 −2.9 TC37125 1946 486 1276 2675 2376 2256 −2.7 TC343211133 1989 1051 2901 3233 3270 −2.6 TC35099 1565 3225 2314 3774 5816 7280−2.6 TC22794 420 153 343 1106 1654 1016 −2.6 TC28206 −519 −812 −715 778784 816 −2.5 TC17374 44879 40619 41419 95128 124767 111416 −2.5 TC1953638 165 264 626 476 617 −2.5 TC39309 708 927 1767 2405 2161 1651 −2.5TC14511 2772 859 1861 2932 4587 3089 −2.4 TC25977 −125 907 −393 1714 9391724 −2.4 TC34555 713 2541 2642 3098 3608 4297 −2.4 TC40318 2484 20403012 5440 5650 5710 −2.4 TC22050 721 421 545 944 1092 1638 −2.4 TC23531264 555 298 677 1076 612 −2.4 TC35434 1150 743 1300 2736 2496 1833 −2.4TC37551 −265 73 −169 118 422 232 −2.4 TC34651 792 2193 2064 3432 37514517 −2.3 TC40365 −286 −312 −315 176 172 252 −2.3 TC26535 4580 119259572 12361 20086 21438 −2.2 TC25372 12 141 −161 348 276 386 −2.2 TC28752816 1567 2442 3958 2783 2378 −2.2 TC21901 1491 754 1326 2284 2539 2382−2.2 TC41250 628 279 660 782 1093 1096 −2.2 TC20836 102 182 514 781 452820 −2.2 TC39607 1263 1289 765 1277 1861 1895 −2.2 TC33236 1991 25883851 5152 4945 5421 −2.1 TC41556 1138 1047 1367 2263 1972 1988 −2.1TC41884 475 55 193 650 406 693 −2.1 TC31627 606 494 1343 1839 1123 2105−2.1 TC35120 1298 1479 752 2993 2032 1705 −2.1 TC37978 664 425 875 14441620 1546 −2.1 TC32191 329 1419 700 2118 1560 2187 −2.0 TC39472 57735966 4650 9742 11750 11019 −2.0 TC36773 2894 3313 4085 5414 7595 6159−2.0 TC38302 459 289 306 621 809 568 −2.0 TC28179 11576 8026 7030 1606314643 19203 −2.0

We claim:
 1. A method of measuring the biological age of a multicellularorganism comprising the steps of: (a) obtaining a sample of nucleic acidisolated from the organism's organ, tissue or cell, wherein the nucleicacid is RNA or a cDNA copy of RNA and (b) determining the geneexpression pattern of a panel of specific sequences within the nucleicacid pool described in (a) that have been predetermined to eitherincrease or decrease in response to biological aging of the organ,tissue or cell, where the gene expression pattern comprises the relativelevel of mRNA or cDNA abundance for the panel of specific sequences. 2.The method of claim 1 wherein the expression patterns of at least tensequences are determined in step (b).
 3. The method of claim 2 whereinthe expression patterns of at least 20 sequences are determined in step(b).
 4. The method of claim 3 wherein the expression levels of at least30 sequences are determined in step (b).
 5. The method of claim 4wherein the expression levels of at least 40 sequences are determined instep (b).
 6. The method of claim 5 wherein the expression levels of atleast 50 sequences are determined in step (b).
 7. The method of claim 1wherein the organism is a mammal.
 8. The method of claim 7 wherein themammal is slected from the group consisting of humans, rats and mice. 9.The method of claim 1 wherein the nucleic acid is isolated from a tissueselected from the group consisting of brain tissue, heart tissue, muscletissue, skin, liver tissue, blood, skeletal muscle, lymphocytes andmucosa.
 10. The method of obtaining biomarkers of aging comprising thesteps of: (a) comparing a gene expression profile of a youngmulticellular organism subject's organ, tissue or cells; a geneexpression profile from a biologically and chronologically agedsubject's organ, tissue or cell; and a gene expression profile from achronologically aged but biologically younger subject's organ, tissue orcell, and (b) identifying gene expression alterations that are observedwhen comparing the young subjects and the chronologically andbiologically aged subjects and are not observed or reduced in magnitudewhen comparing the young subjects and chronologically aged butbiologically younger subjects.
 11. The method of claim 10 wherein oneuses high density oligonucleotide arrays comprising at least 5-10% ofthe subject's genes to compare the subjects gene expression profile. 12.The method of claim 10 wherein the gene expression profile indicates atwo-fold or greater increase or decrease in the expression of certaingenes in chronologically aged subjects.
 13. The method of claim 10wherein the gene expression profile indicated a 3-fold or greaterincrease or decrease in the expression of certain genes inchronologically aged subjects.
 14. The method of claim 10 wherein thegene expression profile indicates a 4-fold or greater increase ordecrease in the expression of certain genes in chronologically agedsubjects.
 15. A method of measuring biological age of muscle tissuecomprising the step of quantifying the mRNA abundance of a panel ofbiomarkers selected from the group consisting of markers W08057,AA114576, 11071777, 11106112, D29016, and M16465.
 16. A method ofmeasuring biological age of muscle tissue comprising the step ofquantifying the mRNA abundance of a panel of biomarkers selected fromthe group consisting of markers described in Tables 1, 2, 15, and 16.17. A method of measuring biological age of brain tissue comprising thestep of quantifying the mRNA abundance of a panel of biomarkers selectedfrom the group consisting of markers M17440, K01347, AA116604 andX16995.
 18. The method of claim 10 wherein the subject is a mammal. 19.The method of claim 18 wherein the mammal is selected from the groupconsisting of humans, mice and rats.
 20. A method of measuringbiological age of brain tissue comprising the step of quantifying themRNA abundance of a panel of biomarkers selected from the groupconsisting of markers described in Tables 5, 6, 9, and
 10. 21. A methodof measuring biological age of heart tissue comprising the step ofquantifying the mRNA abundance of a panel of biomarkers selected fromthe group consisting of markers described in Tables 11, 12, 13 and 14.22. A method for screening a compound for the ability to inhibit orretard the aging process in multicellular organisms tissue, organ orcell comprising the steps of: (a) dividing test organisms into first andsecond mammalian samples; (b) exposing the organisms of the first sampleto a test compound; (c) analyzing tissues, organs or cells of the firstand second samples for the level of expression of a panel of sequencesthat have been predetermined to either increase or decrease in responseto biological aging of the tissue; (d) comparing the analysis of thefirst and second samples and identifying test compounds that modify theexpression of the sequences of step (c) in the first sample such thatthe expression pattern is indicative of tissue, organ or cell that hasan inhibited or retarded biological age.
 23. A method as in claim 22,wherein the organism is a mammal.
 24. The method of claim 23, whereinthe mammal is selected from the group consisting of humans, rats andmice.
 25. A method as in claim 23, wherein the tissue is selected fromthe group consisting of brain tissue, heart tissue, muscle tissue,blood, skeletal muscle, mucosa, skin, lymphocytes and liver tissue. 26.A method of detecting whether a test compound mimics the gene profileinduced by caloric restriction, comprising the steps of: (a) exposing amulticellular organism to the test compound, and (b) measuring theexpression level of a panel of sequences predetermined to eitherincrease or decrease in response to biological aging in a tissue, organor cell of the organism and comparing the measurement to a measurementobtained in the same tissue, organ or cell in calorically restrictedsubjects.
 27. The method of claim 26 wherein the multicellular organismis a mammal.
 28. The method of claim 27 wherein the mammal is selectedfrom the group consisting of humans, rodents and mice.